WO2013188879A1 - Mesure de lipoprotéines sériques - Google Patents
Mesure de lipoprotéines sériques Download PDFInfo
- Publication number
- WO2013188879A1 WO2013188879A1 PCT/US2013/046170 US2013046170W WO2013188879A1 WO 2013188879 A1 WO2013188879 A1 WO 2013188879A1 US 2013046170 W US2013046170 W US 2013046170W WO 2013188879 A1 WO2013188879 A1 WO 2013188879A1
- Authority
- WO
- WIPO (PCT)
- Prior art keywords
- fraction
- ldl
- idl
- sample
- vldl
- Prior art date
Links
- 102000004895 Lipoproteins Human genes 0.000 title claims abstract description 246
- 108090001030 Lipoproteins Proteins 0.000 title claims abstract description 246
- 238000005259 measurement Methods 0.000 title claims description 136
- 210000002966 serum Anatomy 0.000 title claims description 70
- 239000002245 particle Substances 0.000 claims abstract description 354
- 238000000034 method Methods 0.000 claims abstract description 224
- 238000005375 photometry Methods 0.000 claims abstract description 77
- 210000004369 blood Anatomy 0.000 claims abstract description 9
- 239000008280 blood Substances 0.000 claims abstract description 9
- 102100040214 Apolipoprotein(a) Human genes 0.000 claims description 160
- 101710115418 Apolipoprotein(a) Proteins 0.000 claims description 158
- 238000000149 argon plasma sintering Methods 0.000 claims description 148
- 150000002632 lipids Chemical class 0.000 claims description 136
- 238000000926 separation method Methods 0.000 claims description 45
- 238000005119 centrifugation Methods 0.000 claims description 35
- 239000007788 liquid Substances 0.000 claims description 31
- 230000000923 atherogenic effect Effects 0.000 claims description 30
- 239000012530 fluid Substances 0.000 claims description 15
- 101150102415 Apob gene Proteins 0.000 claims description 13
- 230000003287 optical effect Effects 0.000 claims description 9
- 238000005070 sampling Methods 0.000 claims description 9
- 238000004140 cleaning Methods 0.000 claims description 8
- 201000010099 disease Diseases 0.000 claims description 6
- 208000037265 diseases, disorders, signs and symptoms Diseases 0.000 claims description 6
- 238000000432 density-gradient centrifugation Methods 0.000 claims description 5
- 239000011148 porous material Substances 0.000 claims description 5
- 238000002835 absorbance Methods 0.000 claims description 4
- 238000012886 linear function Methods 0.000 claims description 3
- 230000004044 response Effects 0.000 claims description 3
- 241000269627 Amphiuma means Species 0.000 claims 1
- 238000011010 flushing procedure Methods 0.000 claims 1
- GZQKNULLWNGMCW-PWQABINMSA-N lipid A (E. coli) Chemical compound O1[C@H](CO)[C@@H](OP(O)(O)=O)[C@H](OC(=O)C[C@@H](CCCCCCCCCCC)OC(=O)CCCCCCCCCCCCC)[C@@H](NC(=O)C[C@@H](CCCCCCCCCCC)OC(=O)CCCCCCCCCCC)[C@@H]1OC[C@@H]1[C@@H](O)[C@H](OC(=O)C[C@H](O)CCCCCCCCCCC)[C@@H](NC(=O)C[C@H](O)CCCCCCCCCCC)[C@@H](OP(O)(O)=O)O1 GZQKNULLWNGMCW-PWQABINMSA-N 0.000 claims 1
- 208000024172 Cardiovascular disease Diseases 0.000 abstract description 3
- 108010022197 lipoprotein cholesterol Proteins 0.000 abstract description 2
- 108010007622 LDL Lipoproteins Proteins 0.000 description 234
- 102000007330 LDL Lipoproteins Human genes 0.000 description 234
- 108010046315 IDL Lipoproteins Proteins 0.000 description 141
- 108010010234 HDL Lipoproteins Proteins 0.000 description 129
- 102000015779 HDL Lipoproteins Human genes 0.000 description 129
- 108010062497 VLDL Lipoproteins Proteins 0.000 description 109
- 230000006870 function Effects 0.000 description 38
- HVYWMOMLDIMFJA-DPAQBDIFSA-N cholesterol Chemical compound C1C=C2C[C@@H](O)CC[C@]2(C)[C@@H]2[C@@H]1[C@@H]1CC[C@H]([C@H](C)CCCC(C)C)[C@@]1(C)CC2 HVYWMOMLDIMFJA-DPAQBDIFSA-N 0.000 description 36
- 102000018616 Apolipoproteins B Human genes 0.000 description 34
- 108010027006 Apolipoproteins B Proteins 0.000 description 34
- UFTFJSFQGQCHQW-UHFFFAOYSA-N triformin Chemical compound O=COCC(OC=O)COC=O UFTFJSFQGQCHQW-UHFFFAOYSA-N 0.000 description 24
- 238000004364 calculation method Methods 0.000 description 20
- 239000000306 component Substances 0.000 description 19
- 235000012000 cholesterol Nutrition 0.000 description 18
- 238000002298 density-gradient ultracentrifugation Methods 0.000 description 18
- 238000011088 calibration curve Methods 0.000 description 16
- 238000003018 immunoassay Methods 0.000 description 16
- 239000003550 marker Substances 0.000 description 16
- 230000008569 process Effects 0.000 description 15
- 241000894007 species Species 0.000 description 12
- 230000001133 acceleration Effects 0.000 description 11
- 239000000203 mixture Substances 0.000 description 11
- 238000008214 LDL Cholesterol Methods 0.000 description 9
- 238000004458 analytical method Methods 0.000 description 9
- 238000005194 fractionation Methods 0.000 description 9
- 102000005666 Apolipoprotein A-I Human genes 0.000 description 8
- 108010059886 Apolipoprotein A-I Proteins 0.000 description 8
- -1 I DL Proteins 0.000 description 8
- 238000003556 assay Methods 0.000 description 8
- 239000003153 chemical reaction reagent Substances 0.000 description 8
- 238000005481 NMR spectroscopy Methods 0.000 description 7
- 239000000243 solution Substances 0.000 description 7
- 239000000126 substance Substances 0.000 description 7
- 239000000463 material Substances 0.000 description 6
- 102000004169 proteins and genes Human genes 0.000 description 6
- 108090000623 proteins and genes Proteins 0.000 description 6
- FAPWRFPIFSIZLT-UHFFFAOYSA-M Sodium chloride Chemical compound [Na+].[Cl-] FAPWRFPIFSIZLT-UHFFFAOYSA-M 0.000 description 5
- 230000002452 interceptive effect Effects 0.000 description 5
- 102000007592 Apolipoproteins Human genes 0.000 description 4
- 108010071619 Apolipoproteins Proteins 0.000 description 4
- 230000008901 benefit Effects 0.000 description 4
- 238000012417 linear regression Methods 0.000 description 4
- 238000011160 research Methods 0.000 description 4
- 150000003626 triacylglycerols Chemical class 0.000 description 4
- 241001465754 Metazoa Species 0.000 description 3
- 230000034994 death Effects 0.000 description 3
- 231100000517 death Toxicity 0.000 description 3
- 238000001514 detection method Methods 0.000 description 3
- 238000010790 dilution Methods 0.000 description 3
- 239000012895 dilution Substances 0.000 description 3
- 239000000975 dye Substances 0.000 description 3
- 208000019622 heart disease Diseases 0.000 description 3
- 238000002356 laser light scattering Methods 0.000 description 3
- 238000012986 modification Methods 0.000 description 3
- 230000004048 modification Effects 0.000 description 3
- 238000012360 testing method Methods 0.000 description 3
- 238000005199 ultracentrifugation Methods 0.000 description 3
- 101710095342 Apolipoprotein B Proteins 0.000 description 2
- 102100040202 Apolipoprotein B-100 Human genes 0.000 description 2
- 108010074051 C-Reactive Protein Proteins 0.000 description 2
- 229920006362 Teflon® Polymers 0.000 description 2
- 238000004891 communication Methods 0.000 description 2
- 230000003247 decreasing effect Effects 0.000 description 2
- 239000008367 deionised water Substances 0.000 description 2
- 238000003745 diagnosis Methods 0.000 description 2
- 230000003116 impacting effect Effects 0.000 description 2
- 230000000670 limiting effect Effects 0.000 description 2
- 238000000691 measurement method Methods 0.000 description 2
- 208000010125 myocardial infarction Diseases 0.000 description 2
- 150000003904 phospholipids Chemical class 0.000 description 2
- 230000002265 prevention Effects 0.000 description 2
- 239000011780 sodium chloride Substances 0.000 description 2
- 238000004879 turbidimetry Methods 0.000 description 2
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 description 2
- 240000007241 Agrostis stolonifera Species 0.000 description 1
- 108010088751 Albumins Proteins 0.000 description 1
- 102000009027 Albumins Human genes 0.000 description 1
- 108010012927 Apoprotein(a) Proteins 0.000 description 1
- 201000001320 Atherosclerosis Diseases 0.000 description 1
- 241000283690 Bos taurus Species 0.000 description 1
- 241000282472 Canis lupus familiaris Species 0.000 description 1
- 208000017667 Chronic Disease Diseases 0.000 description 1
- 108010004103 Chylomicrons Proteins 0.000 description 1
- 101100055841 Danio rerio apoa1 gene Proteins 0.000 description 1
- 241000283086 Equidae Species 0.000 description 1
- 241000282326 Felis catus Species 0.000 description 1
- 102000009123 Fibrin Human genes 0.000 description 1
- 108010073385 Fibrin Proteins 0.000 description 1
- BWGVNKXGVNDBDI-UHFFFAOYSA-N Fibrin monomer Chemical compound CNC(=O)CNC(=O)CN BWGVNKXGVNDBDI-UHFFFAOYSA-N 0.000 description 1
- 241000282412 Homo Species 0.000 description 1
- 208000010152 Huntington disease-like 3 Diseases 0.000 description 1
- 206010020772 Hypertension Diseases 0.000 description 1
- FFFHZYDWPBMWHY-VKHMYHEASA-N L-homocysteine Chemical compound OC(=O)[C@@H](N)CCS FFFHZYDWPBMWHY-VKHMYHEASA-N 0.000 description 1
- 108010028554 LDL Cholesterol Proteins 0.000 description 1
- 108010033266 Lipoprotein(a) Proteins 0.000 description 1
- 241000124008 Mammalia Species 0.000 description 1
- 101100109141 Mesocricetus auratus APOAI gene Proteins 0.000 description 1
- 241000699670 Mus sp. Species 0.000 description 1
- 241000283973 Oryctolagus cuniculus Species 0.000 description 1
- 241001494479 Pecora Species 0.000 description 1
- 241000288906 Primates Species 0.000 description 1
- 241000700159 Rattus Species 0.000 description 1
- 241000283984 Rodentia Species 0.000 description 1
- VYPSYNLAJGMNEJ-UHFFFAOYSA-N Silicium dioxide Chemical compound O=[Si]=O VYPSYNLAJGMNEJ-UHFFFAOYSA-N 0.000 description 1
- CZMRCDWAGMRECN-UGDNZRGBSA-N Sucrose Chemical compound O[C@H]1[C@H](O)[C@@H](CO)O[C@@]1(CO)O[C@@H]1[C@H](O)[C@@H](O)[C@H](O)[C@@H](CO)O1 CZMRCDWAGMRECN-UGDNZRGBSA-N 0.000 description 1
- 229930006000 Sucrose Natural products 0.000 description 1
- 241000282898 Sus scrofa Species 0.000 description 1
- 239000004809 Teflon Substances 0.000 description 1
- 108010069201 VLDL Cholesterol Proteins 0.000 description 1
- 230000009471 action Effects 0.000 description 1
- 230000003466 anti-cipated effect Effects 0.000 description 1
- 238000013459 approach Methods 0.000 description 1
- 230000003143 atherosclerotic effect Effects 0.000 description 1
- 239000000090 biomarker Substances 0.000 description 1
- 239000012503 blood component Substances 0.000 description 1
- AIYUHDOJVYHVIT-UHFFFAOYSA-M caesium chloride Chemical compound [Cl-].[Cs+] AIYUHDOJVYHVIT-UHFFFAOYSA-M 0.000 description 1
- 150000005829 chemical entities Chemical class 0.000 description 1
- 150000001840 cholesterol esters Chemical class 0.000 description 1
- 239000008119 colloidal silica Substances 0.000 description 1
- 239000003599 detergent Substances 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 206010012601 diabetes mellitus Diseases 0.000 description 1
- 238000002405 diagnostic procedure Methods 0.000 description 1
- 230000002526 effect on cardiovascular system Effects 0.000 description 1
- 238000001962 electrophoresis Methods 0.000 description 1
- 230000003511 endothelial effect Effects 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 230000002255 enzymatic effect Effects 0.000 description 1
- 238000006911 enzymatic reaction Methods 0.000 description 1
- 229950003499 fibrin Drugs 0.000 description 1
- 238000001917 fluorescence detection Methods 0.000 description 1
- 239000000446 fuel Substances 0.000 description 1
- 230000005484 gravity Effects 0.000 description 1
- 239000005556 hormone Substances 0.000 description 1
- 229940088597 hormone Drugs 0.000 description 1
- 230000002209 hydrophobic effect Effects 0.000 description 1
- 230000000977 initiatory effect Effects 0.000 description 1
- 150000002500 ions Chemical class 0.000 description 1
- 210000004185 liver Anatomy 0.000 description 1
- 230000014759 maintenance of location Effects 0.000 description 1
- 230000002503 metabolic effect Effects 0.000 description 1
- 230000000877 morphologic effect Effects 0.000 description 1
- 230000036961 partial effect Effects 0.000 description 1
- 230000002093 peripheral effect Effects 0.000 description 1
- 230000000144 pharmacologic effect Effects 0.000 description 1
- 235000013855 polyvinylpyrrolidone Nutrition 0.000 description 1
- 229920000036 polyvinylpyrrolidone Polymers 0.000 description 1
- 239000001267 polyvinylpyrrolidone Substances 0.000 description 1
- 239000002243 precursor Substances 0.000 description 1
- 238000011045 prefiltration Methods 0.000 description 1
- 238000002360 preparation method Methods 0.000 description 1
- 230000000306 recurrent effect Effects 0.000 description 1
- 230000002829 reductive effect Effects 0.000 description 1
- 238000013207 serial dilution Methods 0.000 description 1
- 230000000391 smoking effect Effects 0.000 description 1
- 239000002904 solvent Substances 0.000 description 1
- 239000012798 spherical particle Substances 0.000 description 1
- 238000010561 standard procedure Methods 0.000 description 1
- 239000005720 sucrose Substances 0.000 description 1
- 239000004094 surface-active agent Substances 0.000 description 1
- 230000009466 transformation Effects 0.000 description 1
- 238000000844 transformation Methods 0.000 description 1
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N15/00—Investigating characteristics of particles; Investigating permeability, pore-volume or surface-area of porous materials
- G01N15/10—Investigating individual particles
- G01N15/14—Optical investigation techniques, e.g. flow cytometry
- G01N15/1434—Optical arrangements
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N1/00—Sampling; Preparing specimens for investigation
- G01N1/28—Preparing specimens for investigation including physical details of (bio-)chemical methods covered elsewhere, e.g. G01N33/50, C12Q
- G01N1/38—Diluting, dispersing or mixing samples
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N15/00—Investigating characteristics of particles; Investigating permeability, pore-volume or surface-area of porous materials
- G01N15/04—Investigating sedimentation of particle suspensions
- G01N15/05—Investigating sedimentation of particle suspensions in blood
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N15/00—Investigating characteristics of particles; Investigating permeability, pore-volume or surface-area of porous materials
- G01N15/06—Investigating concentration of particle suspensions
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
- G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
- G01N33/483—Physical analysis of biological material
- G01N33/487—Physical analysis of biological material of liquid biological material
- G01N33/49—Blood
- G01N33/491—Blood by separating the blood components
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
- G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
- G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
- G01N33/92—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving lipids, e.g. cholesterol, lipoproteins, or their receptors
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N15/00—Investigating characteristics of particles; Investigating permeability, pore-volume or surface-area of porous materials
- G01N15/06—Investigating concentration of particle suspensions
- G01N15/075—Investigating concentration of particle suspensions by optical means
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N15/00—Investigating characteristics of particles; Investigating permeability, pore-volume or surface-area of porous materials
- G01N15/04—Investigating sedimentation of particle suspensions
- G01N15/042—Investigating sedimentation of particle suspensions by centrifuging and investigating centrifugates
- G01N2015/045—Investigating sedimentation of particle suspensions by centrifuging and investigating centrifugates by optical analysis
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N15/00—Investigating characteristics of particles; Investigating permeability, pore-volume or surface-area of porous materials
- G01N15/10—Investigating individual particles
- G01N15/14—Optical investigation techniques, e.g. flow cytometry
- G01N2015/1486—Counting the particles
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
- G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
- G01N33/483—Physical analysis of biological material
- G01N33/487—Physical analysis of biological material of liquid biological material
- G01N33/49—Blood
- G01N33/492—Determining multiple analytes
Definitions
- CHD coronary heart, disease
- Heart disease is a multi -factorial disease and several risk factors such as high blood pressure, smoking, elevated serum low density lipoprotein (LDL) cholesterol, and diabetes are attributed to an increased risk.
- LDL low density lipoprotein
- LDL is known to be directly responsible for the build-up of the plaque within the arterial wall which results in subsequent coronary events. This is further supported by the fact that lowering LDL cholesterol by pharmacological means or lifestyle changes significantly reduces coronary events.
- lowering LDL cholesterol by pharmacological means or lifestyle changes significantly reduces coronary events.
- only 50% of coronary events can be accounted by elevated LDL cholesterol and many studies suggest that coronary events can also occur even in people with normal LDL cholesterol. Therefore, in recent years there has been a surge in research in identifying new risk factors and biomarkers that may explain the CHD risk that cannot not be accounted by traditional risk factors.
- hs-CRP high sensitivity C -Reactive Protein
- homocysteine lipoproteins other than LDL cholesterol, such as low levels of high density lipoproteins (HDL) and its subclasses HDL2 and HDL3, and non-HDL cholesterol which includes intermediate density lipoproteins (IDL), very low density lipoproteins (VLDL,), and lipoprotein(a) [Lp(a)] in addition to LDL cholesterol.
- IDL intermediate density lipoproteins
- VLDL very low density lipoproteins
- Lp(a) lipoprotein(a)
- apo B serum apolipoprotein B
- LDLp LDL particle
- LDL particle number is a significant and independent predictor of cardiovascular endpomts, including CHI) death and myocardial infarction. Most of these studies also have demonstrated that the risk associated with elevated LDL particle number is much higher than that associated with LDL cholesterol.
- LDL particle concentration measurement the measurement of particle concentration (or number) of other lipoproteins such as Lp(a), I DL, VLDL, and HDL would also result in clinical benefit and thus diagnosis and management of heart disease.
- LDLp LDL particle number
- LDLp number (as well as the particle number of other lipoproteins) is not commonly measured because of the following reasons.
- First, measurement of cholesterol is relatively easy since several simple enzymatic methods are available, Second, LDL cholesterol can be conveniently calculated using Friedewald equation [LDL-C Total Cholesterol - (HDL cholesterol + 0.2*triglycerides)].
- the three currently available commercial assays for LDLp are based upon 1) NMR (LipoSeience, NC); 2) ion mobility (Quest Diagnostics, CA); and 3) ultracentrifugation with fluorescence detection (Spectraeell, TX), Furthermore, the above measurement methods do not measure the particle number of all lipoprotein classes. As a result, the particle number measurement methods cannot meet the demand for this widely required test.
- the disclosure provides methods and apparatuses for determining (i.e. counting) lipoprotein particle numbers in a sample.
- the sample is a blood sample.
- the sample is a blood serum sample
- the lipoprotein particle number is determined photometrically. It has been unexpectedly discovered that photometric measurements of lipoproteins in a sample provide a rapid, inexpensive, and accurate determination (count) of lipoprotein particle number. It has also been unexpectedly discovered that photometric measurement can be used effectively to determine (count) lipoprotein particle numbers in sample that has been fractionated to provide for separation of the various classes of lipoprotein particles. The fractionation may be a complete or partial fractionation.
- density-gradient ultracentrifugation is used as the fractionation technique
- light scattering measurements are employed as the photometric measurement. The methods disclosed have been found to pro vide accurate determination (count) of lipoprotein particle number and to be robust in the presence of blood and serum components.
- a general embodiment of the method comprises obtaining a photometric measurement of a serum lipid fraction from a subject and calculating a particle count for at least one serum lipid in the serum lipid fraction, where the particle count is a function of the photometric measurement.
- the photometric measurement is a measurement of light scattering caused by the serum lipid.
- the serum lipid fraction may be fractioned, either completely or partially, prior to the photometric measurement being obtained.
- Another general embodiment of the method comprises obtaining a photometric measurement of a lipoprotein particle in a serum lipid fraction from a subject and calculating a particle count for at least one lipoprotein particle in the lipid fraction, where the particle count is a function of the photometric measurement.
- the photometric measurement is a measurement of light scattering caused by the lipoprotein particle.
- the serum lipid fraction may be fractioned, either completely or partially, prior to the photometric measurement being obtained.
- a more particular embodiment of the method comprises separating at least an LDL traction in a sample, obtaining a measurement of the light scattering from the LDL fraction and calculating a particle count for the LDL fraction, wherein the particle count is a iimction of the measurement of light scattering.
- the method may further comprise separating additional fractions in the sample in addition to the LDL fraction, such as a an HDL fraction, a Lp(a) fraction, an IDL fraction and a VLDL fraction, obtaining a measurement of the light scattering from at least one of the additional fractions and calculating a particle count for each of the additional fraciions from which a light scattering measurement was obtained, wherein the particle count is a function of the measurement of light scattering,
- a more particular embodiment of the method comprises separating at least an LDL fraction and an IDL fraction in a sample, obtaining a measurement of the light scattering from at least one of the LDL and IDL fractions and calculating a particle count for each of the fractions from which a light scattering measurement was obtained, wherein the particle count is a function of the measurement of light scattering.
- the method may further comprise separating additional fractions in the sample in addition to the foregoing, such as a an HDL fraction, a Lp(a) fraction and a VLDL fraction, obtaining a measurement of the light scattering from at least one of the additional fractions and calculating a particle count for each of the additional fractions from which a light scattering measurement was obtained, wherein the particle count is a function of the measurement of light scattering,
- a more particular embodiment of the method comprises separating at least an LDL- fraction, an IDL fraction and a VLDL fraction in a sample, obtaining a measurement of the light scattering from at least one of the fractions and calculating a particle count for each of the fractions from which a light scattering measurement was obtained, wherein the particle count is a function of the measurement of light scattering,
- the method may further comprise separating additional fractions in the sample in addition to the foregoing, such as a Lp(a) fraction and a HDL fraction in a sample,
- the method comprises separating at least an HDL traction, an LDL fraction, an IDL traction and a VLDL fraction in a sample, obtaining a measurement of the light scattering from at least one of the fractions and calculating a particle count for each of the fractions from which a light scattering measurement was obtained, wherein the particle count is a function of the measurement of light scattering.
- the method may further comprise separating an Lp(a) fraction, obtaining a measurement of the light scattering from the Lp(a) fraction and calculating a particle count for the Lp(a) fraction, wherein the particle count is a function of the measurement of light scattering.
- the method comprises separating at least an HDL fraction, an Lp(a) fraction, an LDL fraction, an IDL traction and a VLDL fraction in a sample, obtaining a measurement of the light scattering from at least one of the fractions and calc ulating a particle count for each of the fractions from which a light scattering measurement was obtained, wherein the particle count, is a function of the measurement of light scattering.
- the method comprises separating at least an HDL fraction in a sample, obtaining a measurement of the light scattering from the HDL fraction and calculating a particle count from the HDL fraction, wherein the particle count is a function of the measurement of light scattering,
- the method comprises separating at least an Lp(a) fraction in a sample, obtaining a measurement of the light scattering from the Lp(a) fraction and calculating a particle count from the Lp(a) fraction, wherein the particle count is a function of the measurement of light scattering.
- a particle count is obtained for a fraction other than the LDL fraction, such as a HDL fraction, an Lp(a) fraction, an IDL fraction and a VLDL fraction.
- a general embodiment of the apparatus comprises a containing means for containing a liquid sample having stratified lipid/lipoprotein fractions, a conveying means for conveying the sample from the containing means to a means for counting particles and means for counting particles configured to receive the sample from the containing means by way of the conveying means,
- Another general embodiment of the apparatus comprises a sample vessel containing the sample having stratified lipid/lipoprotein fractions; a liquid conduit positioned to collect the sample from die bottom of the sample vessel; and a light scattering counter positioned to receive the sample from the conduit.
- Also provided is a method of calibrating the measurement of particle count of an atherogenic lipoprotein comprising obtaining a photometric measurement of an atherogenic lipoprotein from a calibration sample, measuring the molar concentration of apolipoprotein B (apoB) in the calibration sample, and calculating a regression between the photometric measurement and the molar concentration of apoB.
- a photometric measurement of an atherogenic lipoprotein from a calibration sample
- measuring the molar concentration of apolipoprotein B (apoB) in the calibration sample calculating a regression between the photometric measurement and the molar concentration of apoB.
- apoB apolipoprotein B
- FIG, 1A is an exemplary particle concentration profile collected with a light scattering detector showing a profile with low amounts of Lp(a) and IDL showing a distinct peak corresponding to HDL, LDL and VLDL.
- FIG, IB is an exemplary particle concentration profile collected with a light scattering detector showing a profile with a distinct Lp(a) peak and also showing distinct HDL, LDL and VLDL peaks.
- FIG, IC is an exemplary particle concentration profile collected with a light scattering detector showing a distinct IDL peak and also showing distinct HDL, LDL and VLDL peaks,
- FIG. I D is an exemplary deconvoluted profile corresponding to the particle concentration profile shown in FIG. 1 A.
- FIG. IE is an exemplary deconvoluted profile corresponding to the particle concentration profile shown in FIG, IB.
- FIG. IF is an exemplary deconvoluted profile corresponding to the particle concentration profile shown in FIG. IC.
- FIG. 2 shows an exemplary particle calibration curve for LDL.
- FIG. 3 shows an exemplary particle calibration curve for Lp(a).
- FIG. 4 shows an exemplary particle calibration curve for IDL
- FIG. 5 shows an exemplary particle calibration curve for VLDL
- FIG, 6 shows an exemplary particle calibration curve for HDL.
- FIG. 7A shows a deconvoluted profile of a sample having a low triglyceride count (94 mg/dL) analyzed under the separation conditions referenced as Condition 2
- FIG. 7B shows a deconvoluted profile of a sample having a low triglyceride count (94 mg dL) analyzed under the separation conditions referenced as Condition 1.
- FIG. 7C shows a deconvoluted profile of a sample having a high triglyceride count (437 mg/dL) analyzed under the separation conditions referenced as Condition 2.
- Fig. 7D shows a deconvoluted profile of a sample having a high triglyceride count (437 mg/dL) analyzed under the separation conditions referenced as Condition 1
- FIG. 8A shows a particle concentration profile collected with a light scattering detector illustrating a profile run under separation Condition 3 for resolution of HDL.
- FIG. SB shows the deconvoluted profile corresponding to the particle concentration profile shown in FIG. 8A.
- FIG. 9 A shows a particle concentration profile collected with a light scattering detector illustrating a profile run under separation Condition 4 for resolution of Lp(a).
- FIG. 9B shows the deconvoluted profile corresponding to the particle concentration profile shown in FIG. 9A.
- FIG. 10 shows a schematic illustration of one embodiment of the apparatus of the present disclosure.
- FIG. 11 shows an exemplary particle concentration profile collected with a light scattering detector showing a normal lipid profile with three well-resolved peaks for the FIDL, LDL, and VLDL fractions.
- FIG. 12 shows an exemplary particle concentration profile collected with a light scattering detector showing a profile with a high LDL lipid profile with three well- resolved peaks for the HDL, LDL, and VLDL fractions.
- FIG. 13 shows an exemplary particle concentration profile collected with a light scattering detector showing a profile with a high Lp(a) lipid profile in which the I .p(a) peak falls between the HDL peak and LDL peak.
- FIG. 14 shows an exemplary particle concentration profile collected with a light scattering detector showing a profile with a high IDL lipid profile in which the IDL peak falls between the LDL peak and VLDL peak.
- FIG. 15 shows the deconvoluted profile corresponding to the particle concentration profile shown in FIG. 1 1.
- FIG. 16 shows the deconvoluted profile corresponding to the particle concentration profile shown in FIG. 12,
- FIG. 17 shows the deconvoluted profile corresponding to the particle concentration profile shown in FIG, 13.
- FIG. 1 8 shows the deconvoluted profile corresponding to the particle concentration profile shown in FIG. 14.
- FIG. 19 shows a linearity graph for HDL.
- FIG. 20 shows a linearity graph for Lp(a).
- FIG. 21 shows a linearity graph for LDL.
- FIG. 22 shows a linearity graph for IDL.
- FIG. 23 shows a linearity graph for VLDL.
- FIG. 24 shows a comparison of LDL particle number as determined by the methods described herein (using Condition 2 as the centrifugation condition) to apo B concentration as determined by the Abbott/Architect C8000 immunoassay,
- FIG, 25 shows a comparison of LDL particle number as determined by the methods described herein (using Condition 2 as the centrifugation condition) to LDL particle number as determined by an NMR. assay (LipoScience).
- FIG. 26 shows a comparison of IDL particle number as determined by the methods described herein (using Condition 2 as the centrifugation condition) as compared to cholesterol concentration in the IDL peak as determined by the VAP assay (Atherotech, Inc.).
- FIG. 27 shows a comparison of VLDL particle number as determined by the methods described herein (using Condition 2 as the centrifugation condition) as compared to cholesterol concentration in the VLDL peak as determined by the VAP assay (Atherotech, Inc.).
- FIG, 28 shows a comparison of HDL particle number as determined by the methods described herein (using Condition 3 as the centrifugation condition) to Apo AI concentration as determined by the Abbott/ Architect C8000 immunoassay.
- FIG. 29 shows a comparison of Lp(a) particle number as determined by the methods described herein (using Condition 4 as the eentrifugation condition) as compared with Lp(a) concentration as determined by the Randox Laboratories Lp(a) immunoassay.
- FIG . 30 shows an exemplary set of curves generated by varying the parameters of the Weibull equation.
- FIG. 31 shows an example of deconvolution of a particle concentration profile collected with a light scattering detector, with the continuous profile being deconvoluted into 14 subcurves.
- FIG. 32 shows an example of grouping and summing the subcurves shown in FIG. 31 into higher level curves representative of the lipoprotein classes.
- the term "individual”, “subject” or “patient ' “ as used herein refers to any animal, including mammals, such as mice, rats, other rodents, rabbits, dogs, cats, swine, cattle, sheep, horses, or primates, and humans.
- mammals such as mice, rats, other rodents, rabbits, dogs, cats, swine, cattle, sheep, horses, or primates, and humans.
- the term may specify male or female or both, or exclude male or female.
- Lipoproteins are spherical particles circulating in the blood whose primary function is to provide fuel in the form of fat and cholesterol. Cholesterol is an essential structural component of cell wail and a precursor to many hormones. Thus all lipoprotein particles consist of a dense hydrophobic core tightly packed with triglycerides (the main source of energy) and cholesterol ester surrounded by a thin, hydrophilic layer consisting of phospholipids, free cholesterol, and unique proteins called apolipoproteins. This structural arrangement allows the easy transport of these particles in the hydrophilic medium of blood from their origin in the gut and liver to the peripheral cells.
- lipoproteins The chemical composition of lipoproteins varies depending upon their function, origin, and metabolic state, and results in different densities and sizes of Lipoproteins. Thus, lipoproteins are primarily classified based on their density into the following classes: HDL, Lp(a), LDL, IDL and VLDL.
- HDL is a lipoprotein rich in proteins.
- LDL is a lipoprotein rich in cholesterol and containing decreased amounts of triglyceride (TG).
- TG triglyceride
- VLDL lipoproteins are rich in TG.
- Lp(a) which is an LDL particle with a unique protein called apolipoprotein(a) attached to the apoB molecule of the, LDL particle through a disulfide bond; Lp(a) particle share many of the characteristics of LDL particles, IDL lipoproteins have a density between LDL and VLDL and are rich in TG but low in cholesterol.
- lipoproteins have similar structural components (i.e., all contain cholesterol, triglycerides, and phospholipids) with unique apolipoproteins their separation for the purpose of quantitation based on chemical composition is difficult, As a result, the different physical parameters of lipoproteins, such as, but not limited to, density and size, are most commonly utilized for separation purposes. Ultraeenlrifhgation and electrophoresis are the most common and accepted separation methods, although methods based on chemical composition have recently emerged.
- the measurement of lipoprotein particle concentration is based on the direct relationship between the number of lipoprotein particles present in a given volume of sample and the area under the lipoprotein peak as determined by the detector.
- lipoproteins are separated based upon their respective densities.
- the HDL migrates to the bottom of the centrifuge tube
- LDL migrates to the middle of the tube
- VLDL migrates to the top of tube.
- Lp(a) migrates between HDL and LDL
- IDL migrates between LDL and VLDL
- the detector such as photometric detector or a light scattering detector as discussed in more detail herein
- the signal from the detector is output as a continuous curve corresponding to particle concentration profile, with peaks corresponding to the various lipoproteins (including HDL and other proteins, Lp(a), LDL, IDL, and VLDL) that are present in the sample.
- FIG. 1A is a profile with low amounts of Lp(a) and IDL showing a distinct peak corresponding to HDL, LDL and VLDL;
- FIG. I B is a profile showing a distinct Lp(a) peak and also showing distinct HDL, LDL and VLDL peaks:
- FIG. 1C is a profile showing a distinct IDL peak and also showing distinct HDL, LDL- and VLDL peaks.
- the separation of lipoprotein peaks from each other does not reach baseline separation since the separation procedure used, in this case uitracentrifugation, is a rapid non-equilibrium density gradient ultracentrifugation suitable for higher throughput required by a clinical laboratory,
- quantitation of each lipoprotein requires a mathematical deconvolution process to calculate the corresponding areas under the respective lipoprotein peaks.
- the deconvolution process quantifies lipoprotein peaks in terras of their respective peak areas, which can be used to determine particle concentration as described herein.
- the deconvolution process uses a general purpose computer to record the output from the detector.
- the deconvolution process is based upon the peak shapes (peak widths at half-height and exponential tails) and sizes (peak height) expected and observed from the isolated individual lipoprotein classes from preparative ultracentrifugation.
- Fitted subcurves are configured to align with the shapes (peak width and exponential tail) and size (peak height) of the peaks on the main continuous curve, Furthermore, subcurve peak positions and shapes and sizes are adjusted so as to minimize the difference between the total area under the main continuous response curve from the detector and sum of the areas under all subcurves.
- the software uses a least-square non-linear regression analysis to minimize the area between the main response curve irom the detector and sum of the subcurves corresponding to individual lipoprotein peaks.
- FIGS. 1D-F Exemplary deeonvoluted profiles corresponding to raw profiles generated from the output of the detector as shown in FlCtS. 1A-C are shown in FIGS. 1D-F, As can be seen, the deconvolution process generates subcurves for the lipoprotein classes discussed herein, From such subcurves, the area under each subcurve is calculated as is known in the art.
- each lipoprotein class requires a separate calibration curve.
- each atherogenic lipoprotein particle contains one and only one apo B molecule and that each particle of HDL contains from 2-5 particles of apo Al .
- the number of lipoprotein particles in a given fraction can be calculated if the marker concentration in that fraction is known.
- Fractions are collected for analysis of the marker and the amount of marker in the sample is determined (such as through the use of an immunoassay) in rag/dL. Since the volume of the fraction is known, the concentration of marker in mg may be determined. The molar concentration of marker is then determined using the molecular weight of the marker, In addition, the area under a given lipoprotein curve is directly proportional to the number or concentration of lipoprotein particles, Thus, if the area under a lipoprotein curve is calibrated using materials with known amount of a specific marker, one can calculate the amount of the marker in a lipoprotein peak of unknown patient (in moles) using calibration curve method (as commonly used for many diagnostic tests) and thus the number of LDL or other lipoprotein particles (using Avogadro's concept).
- a specific example of the calibration procedure is provided using LDL as an example. Calibration procedures tor the remaining atherogenic lipoproteins will be carried out in the same manner.
- fresh patients serum samples with a wide ranging apo B concentration previously determined using immunoassay methods
- the calibration samples are subject to separation as described herein; in one embodiment, the separation and analysis procedure for the calibration samples is the same as the separation procedure used for determining lipoprotein particle concentration in an unknown sample (for example, Conditions 1 and/or 2 as described herein). Rather than analyzing the centrifugate using a photometric detector, the fractions are collected for measurement of the concentration of apo B, the specific marker.
- any method of apo B measurement may be used, in one aspect, an immunoassay method, such as the Abbott/ Architect C8000 system, is used to determine apo B amount in mg/dL.
- concentration of apo B in absolute mg in each fraction can be calculated by knowing the volume of each fraction (which can be measured easily).
- profile curves generated for example profile curves from the same sample, one can detennine which of the examined fractions correspond to the LDL peak (or any desired lipoprotein peak).
- the fractions corresponding to LDL are summed to yield a final apo B amount.
- the apo B amount is used as Y axis and the LDL peak area as X-axis to plot the calibration curve. The process is repeated for each sample to generate a calibration curve.
- equation 1 is used
- Y is the LDL, apo B concentration which is to be determined
- m is the slope of calibration curve
- x is the LDL peak area in V- min.
- FIG. 2 An example of calibration curve for LDL is shown in FIG. 2.
- Exemplary calibration curves for Lp(a), IDL and YLDL are shown in FIGS. 3-5.
- the peak area represents the volt-minutes under the peak obtained using a light scattering detector after the LDL traction had been separated from the other serum components by density-gradient centrifugation. ApoB mass in the LDL fraction was determined by commercial immunoassay.
- ZLDL s the LDL particle number or concentration (nmoi/L)
- V actual serum volume used in ⁇ 8
- W 3 poB molecular weight of apo B (550,000 Da)
- HDL molecular weight of apo B (550,000 Da)
- apo AI is used as the marker.
- the number of Apo AI molecules on HDL particle is known to vary from 2 to 5.
- FIG. 6 An example of calibration curve for HDL is shown in FIG, 6. The peak area represents the volt-minutes under the peak obtained using a light scattering detector after the LDL fraction had been separated from the other serum components by density-gradient centrifugation. Apo AI mass in the HDL fraction was determined by commercial immunoassay.
- equation 1 In order to find apo B concentration in LDL of unknown sample, equation 1 is used as above, but the values of Y and x are as defined below,
- Y is the HDL apo AI concentration which is to be determined.
- x is the HDL peak area in V ⁇ min.
- ZHDL A/(V x (3 x APOAI)
- ZHDL is the HDL particle number or concentration ( ⁇ /L)
- a : HDL Apo AI concentration in mg x 10 z
- V actual serum volume used in ⁇ .1 ⁇
- the lipid is a lipoprotein
- the lipid is a lipoprotein selected from the group consisting of HDL, Lp(a), LDL, IDL and VLDL; the particle number for one or more of the lipoproteins may be determined.
- the sample is a blood sample.
- the sample is a blood serum sample.
- light scattering measurements are employed as the photometric measurement.
- a general embodiment of the method comprises obtaining a photometric measurement of a lipid fraction from a sample and calculating a particle count for the lipid fraction, where the particle count is a function of the photometric measurement.
- the method may further comprise separating a sample into a plurality of lipid fractions to facilitate the measurement.
- the lipid is a lipoprotein.
- the lipid is a lipoprotein selected from the group consisting of HDL, Lp(a), LDL, IDL and VLDL; the particle number for one or more of the lipoproteins may be determined, in one aspect of this embodiment, a given lipid fraction contains only a single lipid species or predominately a single species of lipid, such as, for example. LDL,
- the photometric measurement is a measurement of light scattering caused by the lipid fraction.
- the sample may be fractioned, either completely or partiall , prior to the photometric measurement being obtained.
- Another general embodiment of the method comprises subjecting a sample from a subject containing a lipid to a fractionation technique, the fractionation technique resulting in a plurality of fractions, wherein at least one of the fractions contains a lipid.
- a fraction containing a lipid is referred to herein as a lipid fraction.
- a single sample may be fractionated into one, two, three or n ih lipid fractions. Not every fraction separated need contain a lipid.
- a single fraction contains a single lipid or predominately a single lipid, In addition, in one aspect of this embodiment, a single fraction contains more than one lipid.
- the method comprises separating a first lipid fraction in a sample, obtaining a photometric measurement of a lipid in the first lipid fraction and calculating a particle count for the lipid in the first lipid fraction, where the particle count is a function of the photometric measurement.
- Such a method may further comprise separating a second, third and n ih lipid fraction in a sample, obtaining photometric measurement for at least one of the second, third and n ih lipid fractions and calculating a particle count for at least one of the lipids contained in the second, third and n lipid fractions, wherein the particle count is a function of the photometric measurement.
- the lipid is a lipoprotein.
- the lipid is a lipoprotein selected from the group consisting of LDL, Lp(a), LDL, IDL arid VLDL; the particle number for one or more of the lipoproteins may be determined.
- the method comprises obtaining a measurement of light scattering of a lipid traction from a subject and calculating a particle count for at least one lipid in the lipid fraction, where the particle count is a function of the measurement of light scattering, in one aspect of this embodiment, the lipid i a lipoprotein, in another embodiment, the lipid is a lipoprotein selected from the group consisting of LDL, Lp(a), LDL, IDL and VLDL; the particle number for one or more of the lipoproteins may be determined.
- the lipid fraction contains only a single lipid species, such as, for example, LDL. The lipid fraction may be fractioned, either completely or partially, prior to the photometric measurement being obtained.
- Another general embodiment of the method comprises subjecting a sample from a subject containing a lipid to a fractionation technique, the fractionation technique resulting in a plurality of subdivisions of the sample, wherein at least one of the subdivisions contains a lipid.
- a subdivision containing a lipid is referred to herein as a lipid t action.
- a single sample may be .fractionated into one, two. three or ⁇ ⁇ 3 ⁇ lipid fractions. Not every fraction separated need contain a lipid.
- the method comprises separating a first lipid fraction in a sample, obtaining a measurement of light scattering of a lipid in the first lipid fraction and calculating a particle count for the lipid in the first lipid fraction, where the particle count is a function of the measurement of light scattering.
- Such a method may further comprise separating a second, third and n lipid fraction in a sample, obtaining a measurement of light scattering for at least one of the second, third and n ih lipid fractions and calculating a particle count for at least one of the lipids contained in the second, third and n ,h lipid fractions, wherein the particle count is a function of the measurement of light scattering.
- the lipid is a lipoprotein.
- the lipid is a lipoprotein selected from the group consisting of LDL, Lp(a), LDL, IDL and VLDL; the particle number for one or more of the lipoproteins may be determined.
- one or more of the plurality of lipid fractions contain a lipoprotein
- two or more, three or more, four or more or five or more of the lipid fractions contain a lipoprotein.
- One or more lipid fractions may contain the same lipoprotein and the fractions be considered together when determining the particle number for the lipoprotein.
- the fractions containing the same lipoprotein are considered together using a de-convolution algorithm as described, herein.
- a single lipid fraction may contain a single lipoprotein.
- a single lipid fraction may contain substantially a single lipoprotein.
- the lipid is referred to herein as a lipoprotein for simplicity.
- the methods described herein may be used for other serum lipids as well.
- the lipoproteins in the first, second, third and/or n tn lipid fractions may be separated based on density of the lipoprotein contained in each fraction.
- the first, second, third and/or n !h lipid fractions contain only a single species of lipoprotein or contain substantially only a single species of lipoprotein.
- substantially as used herein with reference to a particular species of lipoproteins or other chemical entity means that the species of lipoprotein in a given fraction comprises 75% or more of the total lipoprotein present in the fraction (as measured on a weight to weight basis), in one embodiment, the species of lipoprotein in a given fraction comprises 85% or more of the total lipoprotein present in the fraction (as measured on a weight, to weight basis).
- the species of lipoprotein in a given fraction comprises 90% or more of the total lipoprotein present in the fraction (as measured on a weight to weight basis), in another embodiment, the species of lipoprotein in a given fraction comprises 95% or more of the total lipoprotein present in the fraction (as measured on a weight to weight basis). In another embodiment, the species of lipoprotein in a given fraction comprises 97% or more of the total lipoprotein present in the fraction (as measured on a weight to weight basis). In another embodiment, the species of lipoprotein in a given fraction comprises 98% or more of the total lipoprotein present in the fraction (as measured on a weight to weight basis). In another embodiment, the species of lipoprotein in a given fraction comprises 99% or more of the total lipoprotein present in the fraction (as measured on a weight to weight basis).
- more than one of the first, second, third and or n ih lipid fractions may each contain a single lipoprotein or substantially a single lipoprotein, such as, but not limited to, HDL, Lp(a), LDL, IDL and VLDL, and be considered together in the calculations described herein.
- the 10 !h to 13 th lipid fraction may each contain LDL or substantially contain LDL and be considered together in the calculations described herein for determining the particle number of LDL,
- the first, second, third and/or n :fi lipid fractions may contain more than one lipoprotein in such fractions, such as, but not limited to, HDL, Lp(a), LDL. IDL and VLDL, and each fraction containing such lipoprotein or substantially such lipoprotein may be considered together in the calculations described herein.
- the 10 1 to 13 ' lipid fraction may each contain LDL or substantially contain LDL and be considered together in the calculations described herein for determining the particle number of LDL and the 14 th to 15 !h lipid fractions may contain IDL or substantially contain IDL and be considered together in the calculations described herein for determining the particle number of IDL.
- the 2 d to 5 th lipid fraction may each contain HDL or substantially contain HDL and be considered together in the calculations described herein for determining the particle number of HDL
- the 10 lh to 13 th lipid fraction may each contain LDL or substantially contain LDL and be considered together in the calculations described herein for determining the particle number of LDL
- the 14 th to 15 th lipid fractions may contain IDL or substantially contain IDL and be considered together in the calculations described herein for determining the particle number of IDL.
- tbe'2 cd to 5 th lipid fraction may each contain HDL or substantially contain HDL and be considered together in the calculations described herein for determining the particle number of HDL
- the 7 th to 9 ih lipid fraction may each contain Lp(a) or substantially contain Lp(a) and be considered together in the calculations described herein for determining the particle number of Lp(a)
- the 10 th to 13 th lipid fraction may each contain LDL or substantially contain LDL and be considered together in the calculations described herein for determining the particle number of LDL
- the 14 ih to 15 th lipid fractions may contain IDL or substantially contain IDL and be considered together in the calculations described herein for determining the particle mrmber of IDL
- the 2 cd to 5 sh lipid fraction may each contain HDL or substantially contain HDL and be considered together in the calculations described herein for determining the particle number of HDL
- the 7 m to 9 ⁇ lipid fraction may each contain Lp(a) or substantially contain Lp(a) and be considered together in the calculations described herein for determining the particle number of Lp(a)
- the 10 th to 13 th lipid fraction may each contain LDL or substantially contain LDL and be considered together in the calculations described herein for determining the particle number of LDL
- the 14 th to 1 5 th lipid fractions may contain IDL or substantially contain IDL and be considered together in the calculations described herein for determining the particle number of IDL
- the 17 ti3 ⁇ 4 to 18 th lipid fractions may contain VLDL or substantially contain VLDL and be considered together in the calculations described herein for determining the particle number of VLDL.
- the terms include the concept of adding together the amounts of a given lipoprotein, class in more than one physical subdivision of the sample collected as a result of the fractionation technique.
- the term “separating at least an LDL fraction in a sample” includes the concept of separating a sample into one or more physical fractions by a fractionation technique and adding together the LDL content in one or more of such subdivisions of the sample to determine the LDL fraction.
- the method comprises separating at least an LDL fraction in a sample, obtaining a measurement of the light scattering from the LDL fraction and calculating a particle count for the LDL fraction, wherein the particle count is a function of the measurement of light scattering.
- the method may further comprise separating at least one additional fraction in addition to an LDL fraction.
- Such additional fraction may include at least one of an HDL fraction, an Lp(a) fraction, an IDL fraction and a VLDL fraction.
- the additional fraction is an IDL fraction.
- the additional fractions are an Lp(a) fraction and IDL fraction
- the additional fractions are an Lp(a) fraction, an IDL fraction and a VLDL fraction.
- the additional fractions are an HDL fraction, an Lp(a) fraction and an IDL fraction. In another aspect, the additional fractions are an HDL fraction, an IDL- fraction and a VLDL fraction. In another aspect, the additional fractions are an HDL fraction, an Lp(a) fraction, an IDL fraction and a VLDL fraction. In another aspect, a particle count from only the LDL fraction is calculated,
- the method comprises separating at least an HDL fraction in a sample, obtaining a measurement of the light scattering from the HDL fraction and calculating a particle count for the HDL fraction, wherein the particle count is a functiono of the measurement of light scattering.
- the method may further comprise separating at least one additional fraction in addition to an HDL fraction.
- Such additional fraction may include at least one of an Lp(a) fraction, a LDL fraction, an IDL fraction and a VLDL fraction.
- the additional fraction is an LDL fraction.
- the additional fractions are an Lp(a) fraction and LDL fraction.
- the additional fractions are an Lp(a) fraction, an LDL fraction and an IDL fraction.
- the additional fractions are an Lp(a) fraction, a LDL fraction, an IDL fraction and a VLDL fraction.
- a particle count from only the HDL fraction is calculated.
- the method comprises separating at least an Lp(a) fraction in a sample, obtaining a measurement of the light scattering from the Lp(a) fraction and calculating a particle count for the Lp(a) fraction, wherein the particle count is a function of the measurement of light scattering.
- the method may further comprise separating at least one additional fraction in addition to an Lp(a) fraction.
- Such additional fraction may include at least one of an HDL fraction, a LDL fraction, an IDL fraction and a VLDL fraction.
- the additional fraction is an LDL fraction
- the additional fractions are a HDL fraction and a LDL fraction
- the additional fractions are a HDL fraction, an LDL fraction and an IDL fraction
- the additional fractions are HDL fraction, a LDL fraction, an IDL fraction and a VLDL fraction.
- a particle count from only the Lp(a) fraction is calculated.
- the method comprises separating at least an LDL fraction and an IDL iraction in a sample, obtaining a measurement of the light scattering from at least one of the LDL or IDL fractions and calculating a particle count for each of the fractions from which a light scattering measurement was obtained, wherein the particle count is a function of the measurement of light scattering,
- a light scattering measurement and a particle count are obtained for both the LDL and IDL fractions.
- a light scattering measurement and a particle count are obtained for only the LDL fraction or the IDL fraction.
- a light scattering measurement and a particle count are obtained for only the LDL fraction,
- the method comprises separating at least a Lp(a) fraction, an LDL- fraction and an IDL fraction in a sample, obtaining a measurement of the light scattering from at least one of the Lp(a), LDL and IDL fractions and calculating a particle count for each of the fractions from which a light scattering measurement was obtained, wherein the particle count is a function of the measurement of light scattering.
- a light scattering measurement and a particle count are obtained for each of the Lp(a), LDL and IDL fractions.
- a light scattering measurement and a particle count are obtained for each of the LDL and IDL fractions.
- a light scattering measurement and a particle count are obtained for each of the Lp(a) and LDL fractions, in another aspect of this embodiment, a light scattering measurement and a particle count are obtained for only the LDL fraction and the IDL fraction. In another aspect of this embodiment, a light scattering measurement and a particle count are obtained for only the LDL fraction.
- the method comprises separating at least an LDL fraction, an IDL and a VLDL fraction in a sample, obtaining a measurement of the light scattering from at least one of the LDL, IDL and V LDL fractions and calculating a particle count for each of the fractions from which a light scattering measurement was obtained, wherein the particle count is a function of the measurement of light scattering,
- a light scattering measurement and a particle count are obtained for each of the LDL, iDL and VLDL fractions
- a light scattering measurement and a particle count are obtained for each of the LDL and IDL fractions.
- a light scattering measurement and a particle count are obtained for only the LDL fraction and the IDL fraction.
- a light scattering measurement and a particle count are obtained for only the LDL fraction.
- the method comprises separating at least an HDL fraction, an LDL fraction, an IDL and a VLDL fraction in a sample, obtaining a measurement of the light scattering from at least one of the HDL, LDL, IDL and VLDL fractions and calculating a particle count for each of the fractions from which a light scattering measurement was obtained, wherein the particle count is a function of the measurement, of light scattering.
- a light scattering measurement and a particle count are obtained for each of the HDL, LDL, ID L and VLDL fractions.
- a light scattering measurement and a particle count are obtained for each of the LDL, IDL and VLDL fractions.
- a light scattering measurement and a particle count are obtained for each of the LDL and IDL fractions, In another aspect of this embodiment, a light scattering measurement and a particle count are obtained for only the HDL fraction. LDL fraction, the IDL fraction or the VLDL fraction, in another aspect of this embodiment, a light scattering measurement and a particle count are obtained for only the LDL fraction.
- the method comprises separating at least an HDL fraction, an Lp(a) fraction, an LDL fraction, an IDL and a VLDL fraction in a sample, obtaining a measurement of the light scattering from at least one of the HDL, Lp(a), LDL, IDL and VLDL fractions and calculating a particle count for each of the fractions from which a light scattering measurement was obtained, wherein the particle count is a function of the measurement of light scattering.
- a light scattering measurement and a particle count are obtained for each of the HDL, Lp(a), LDL, IDL and VLDL fractions.
- a light scattering measurement and a particle count are obtained for each of the LDL, IDL and VLDL fractions. In one aspect of this embodiment, a light scattering measurement and a particle count are obtained for each of the LDL and IDL fractions. In another aspect of this embodiment, a light scattering measurement and a particle count are obtained for only the HDL fraction, LDL fraction, the IDL fraction or the VLDL, fraction. In another aspect of this embodiment, a light scattering measurement and a particle count are obtained for only the LDL fraction.
- a particle count is obtained for only the LDL fraction
- a particle count is obtained for the LDL fraction and at least one additional fraction.
- Such additional fraction may be a HDL fraction, an Lp(a) fraction, an IDL fraction, a VLDL fraction or any combination of the foregoing.
- the additional fraction is an HDL fraction.
- the additional fraction is an Lp(a) fraction.
- the additional fraction is an IDL fraction.
- the additional fraction is a VLDL fraction.
- the additional fraction is an IDL fraction and an Lp(a) fraction.
- the additional fraction is a HDL. , fraction, an IDL fraction and an Lp(a) fraction.
- the additional traction is a HDL. fraction, an IDL fraction, an Lp(a) fraction and a VLDL fraction.
- the additional fraction is an IDL fraction, an Lpfa) fraction and a VLDL fraction.
- a particle count is obtained for only the HDL fraction.
- a particle count is obtained for the HDL fraction and at least one additional fraction.
- Such additional traction may be an Lp(a) fraction, an LDL fraction, an IDL fraction, a VLDL fraction or any combination of the foregoing.
- the additional fraction is an LDL fraction,
- the additional fraction is an Lp(a) fraction, in one aspect of the foregoing methods, the additional fraction is an IDL fraction, in one aspect of the foregoing methods, the additional fraction is a VLDL fraction.
- the additional fraction is an LDL fraction.
- the additional fraction is an Lp(a) fraction. In one aspect of the foregoing methods, the additional fraction is an Lp(a) fraction and an LDL traction, In one aspect, of the foregoing methods, the additional fraction is an Lp(a) fraction, an LDL fraction and an IDL fraction. In one aspect of the foregoing methods, the additional fraction is an Lp(a) fraction, an LDL. fraction, an IDL fraction and a VLDL fraction.
- a particle count is obtained for only the Lp(a) fraction, In one aspect of the foregoing methods, a particle count is obtained for the Lp(a) fraction and at least one additional fraction.
- Such additional fraction may be a HDL fraction, an LDL fraction, an IDL fraction, a VLDL fraction or any combination of the foregoing.
- the additional traction is a HDL, fraction.
- the additional fraction is an LDL fraction.
- the additional fraction is an IDL fraction.
- the additional fraction is a VLDL fraction.
- the additional fraction is an Lp(a) fraction and an LDL iraction. In one aspect of the foregoing methods, the additional fraction is an Lp(a) fraction, an LDL fraction and an IDL fraction. In one aspect of the foregoing methods, the additional fraction is an Lp(a) fraction an LDL iraction, an IDL fraction and a VLDL fraction.
- Atherogenic lipoproteins are counted.
- Such an embodiment will comprise obtaining a measurement of light scattering from at least one atherogenic lipoprotein fraction and calculating a particle count for each of the atherogenic lipoprotein fractions from which a light scattering measurement was obtained, wherein the particle count is a function of the measurement of light scattering.
- the atherogenic lipoprotein in such fractions may be selected from the group consisting of: Lp(a), LDL, IDL, and VLDL, in a specific embodiment the atherogenic lipoprotein is LDL. in another specific embodiment the atherogenic lipoprotein is Lp(a).
- Lp(a) is known to being strongly predictive of cardiovascular disease, yet there are very few methods by which Lp(a) can be easily and accurately measured in serum samples.
- the subject may be any animal having lipoproteins to be measured, in the clinical setting (he subject will often be a human patient, although it is conceivable that the subject will be a non-human animal in the veterinary setting.
- the subject may be human or non-human animal in the research setting.
- the animal in the research setting may be, for example, any commonly used model organism.
- the lipid fraction from the subject will comprise a number of lipoproteins, such as an HDL, an Lp(a), an LDL, an IDL, and/or a VLDL.
- the various lipoproteins may be separated into at least one lipoprotein fractions as described herein.
- the lipoprotein fraction may be substantially pure such that it will be sufficiently free from other components that could affect the photometric measurement that a quantitative value for the lipoprotein in the lipid fraction can be obtained.
- Non-interfering components thai do not affect the photometric measurement may be present,
- the fraction will not be completely free of interfering components in every embodiment.
- lipoprotein fractions may be fractionated on the basis of density, there may be overlap between adjacent lipoprotein fractions.
- the lipid fraction consists essentially of serum components. Irs such embodiments the fraction contains no additional reagents, dyes, or other substances that may be added to facilitate measurement. This is possible in such embodiments because, unlike many other methods of quantifying serum lipids, including but not limited to lipoproteins, many embodiments of the photometric methods disclosed herein do not require the addition of reagents, dyes, fluorochromes, or the like. Any such artificially introduced substances that facilitate measurements are referred to herein as "analytical reagents.
- the serum lipid fractions generated contains no substantial amount of analytical reagents, such that any analytical reagents present are present in sufficiently low concentrations that they do not affect the measurements, in other embodiments the lipoprotein fraction contains no analytical reagent.
- the particle count is calculated as a function of a photometric measurement.
- the photometric measurement is light scattering.
- the function is approximately linear.
- the photometric measurement will be in the form of a curve, typically representing the relationship between run time and the readout of the detector. Characteristics of such curves generated from the photometric measurement include peak height and peak area; such characteristics may be used to calculate a particle number. Peak area is calculated in a variety of ways, most often simply by multiplying the peak height by half of the distance from trough to trough (as if the peak were a triangle). In certain embodiment, software is provided with measuring devices that automatically computes peak area.
- deconvolution transformations may be performed to determine a poorly resolved peak area. Such methods involve taking the area of an aggregate peak and subtracting the contribution of one peak (generally the better resolved peak) to determine the area of the remaining peak.
- Deconvolution is commonly used to resolve small peaks from larger adjacent peaks. In such cases often the smaller peak is only visible as a trough between two larger adjacent peaks, wherein the trough is not as deep as expected.
- the process comprises extrapolating the expected area under the trough between the larger peaks, subtracting the expected area of the trough from the actual area of the actual trough, wherein ihe difference in areas is the area under the smaller peak.
- FIG. 8-1 1 Examples of small lipoprotein peaks calculated by deconvolution are shown in Figures 8-1 1 .
- the heavy black line shows actual light scattering values.
- the thinner lines show extrapolated peaks for each of the fractions (from left to right: HDL, Lp(a), LDL. iDL, and VLDL).
- the shaded peak is the IDL peak, calculated by deconvolution of the LDL and VLDL peaks.
- the peak marked with horizontal hash lines is the Lp(a) peak, calculated by deconvolution of the HDL and LDL peaks.
- the photometric measurement is light scattering
- Light scattering may be measured over any detection arc, for example 360°, 180°, 90°, or 45°. in a specific embodiment light scattering is measured over a 90° detection arc.
- Light scattering can be measured by various means known in the art.
- light scattering is measured using a laser light scattering detector,
- the detector may be a fixed-angle detector or a multi-angle detector.
- the amount of light scattering is approximately proportional to the number of particles per unit volume.
- scattering is measured over a set arc. for example 360°, 180°, 90°, or 45°. in a specific embodiment light scattering is measured over a 90° detection arc.
- the particle count is an approximately linear function of light scattering, although the functions may differ depending on which lipoprotein fraction is being measured. The function can be determined by the calibration methods described below.
- Some embodiments of the method comprise measuring the light scattering of more than one lipoprotein traction, such that the light scattering of the highest density fraction to be measured is measured before the others, in some such embodiments the light scattering of each fraction is measured in order of descending density. That is to say that the light scattering of the fractions would be measured in the following order, with the understanding that not all of the listed fractions need he measured: HDL, Lp(a), LDL, IDL and VLDL, As an illustrative example, if only LDL and VLDL are to be measured, LDL would be measured first, followed by VLDL.
- the sample is prepared by density- gradient ultracen iugation, and the sample is drained from the bottom of a tube used for such centrifugation such that the highest densiiy fractions are collected first and sent to a light scattering counter.
- Another embodiment of the method comprises measuring the particle count of a lipoprotein, fraction of a sample in any of the apparatuses disclosed below.
- lipid fractions in a sample in a particular embodiment, vertical spin density gradient ultracentrifugation is used to separate lipid fractions in a sample.
- the lipid is a lipoprotein.
- any separation means known in the art may be used.
- the lipoprotein particles are separated in the following order (from the bottom of the density gradient to the top of the density gradient): HDL, Lp(a), LDL, IDL and VLDL.
- a variety of density gradient ultracentrifugation conditions may be used.
- the composition of the density gradient may impact the separation between various lipoprotein species. The following are illustrated by way of example only and should not he interpreted as limiting the scope of the separation techniques to density gradient ultracentrifugation or as limiting the conditions employed in density gradient ultracentrifugation ⁇ o those conditions specified.
- certain a given fraction may contain more than one type of serum lipoprotein
- This phenomenon may be caused by several factors, including factors related to the concentration of the various lipoprotein particles in a sample, the separation technique, such as, but not limited to, density gradient ultracentrifugation, and the equipment used in the separation itself.
- the separation technique such as, but not limited to, density gradient ultracentrifugation, and the equipment used in the separation itself.
- specific density gradient ultracentrifugation conditions may be employed to provide maximum resolution of the various lipoprotein classes (such as for example, LDL, IDL and V LDL or HDL and Lp(a)) or may be employed to provide maxim urn resolution of a single lipoprotein (such as HDL, Lp(a) and/or LDL).
- the density gradient ultracentrifugation conditions and parameters are varied to provide maximum resolution of each of the various lipoprotein classes, in another embodiment, the density gradient ultracentrifugation conditions and parameters are varied to provide maximum resolution of one or more specific lipoprotein classes. In still another embodiment, the density gradient ultracentrifugation conditions and parameters are varied to provide maximum resolution of HDL. In still another embodiment, the density gradient ultracentrifugation conditions and parameters are varied to provide maximum resolution of Lp(a). In still another embodiment, the density gradient ultracentrifugation conditions and parameters are varied to provide maximum resolution of LDL.
- Conditions and parameters that may be varied include, but are not limited to, density of the layers comprising the density gradient, volume of the layers comprising the density gradient, centrifugation time settings, acceleration setting (impacting the time it takes for the centrifuge to reach a set RPM), deceleration settings (impacting the time it takes for the centrifuge to come to a stop from the set RPM at the end a specified time setting), speed of the centrifuge (measured in RPM) and temperature of the centriiugation run.
- acceleration setting impacting the time it takes for the centrifuge to reach a set RPM
- deceleration settings impacting the time it takes for the centrifuge to come to a stop from the set RPM at the end a specified time setting
- speed of the centrifuge measured in RPM
- temperature of the centriiugation run The various parameters discussed above may be varied singly or in any combinatio desired,
- the density gradient comprises two layers of gradient material (referred to as a top and bottom layer).
- a commonly used density gradient material is Br.
- Other commonly used density gradient materials include cesium chloride, sucrose, and colloidal silica particles coated with polyvinylpyrrolidone (such as the product sold as Pereoll®). Any density gradient solution known in the art to create the required density range may be used, Centriiugation will be performed in an appropriate vessel, such as a centrifuge tube.
- a variety of suitable centrifuge tubes are commercially available, for example from Beckman-Couiter, of Brea, California, in a specific embodiment separation is achieved using a single spin.
- the density of the bottom layer ranges from 1.10 to 1.40 g/ml, from 1 ,15 to 1.30 g ml or from 1.15 to 1.25 g/ml and the density of the top layer ranges from 0,5 to 1.2 g/ml, from 1.0 to 1 , 15 g/ml or from 1.0 to .1.10 g/mi.
- the density of the bottom layer is 1 ,21 g/mi or 1.30 g/ml and the density of the top layer is 1.05 g/ml.
- the volume of the bottom layer ranges from 0,2 to 4.0 ml, from 0.8 to 2,5 mi or from 1 to 2 m!
- the volume of the top layer ranges from 1 to 4.8 ml, from 1.2 ml to 3.0 ml or from 3.0 to 4.0 ml.
- the volume of the bottom layer is 2 ,0 ml or 1.0 ml and the volume of the top layer is 2.90 nil or 3.9 ml.
- the settings for the ultracentrifuge are varied as follow: (i) centriiugation time from 10 to 70 minutes (note that centrifugation time does not include the time required for deceleration of the centrifuge rotor), from 15 to 50 minutes or from 20 to 40 minutes; (ii) centrifugation speed from 50,000 RPM to 75,000 RPM or 60,000 to 70,000 RPM; and (iii) centrifugation temperature from 15 to 30 degrees Celsius or from 20 to 25 degrees Celsius.
- the acceleration and deceleration settings are selected provide appropriate acceleration and deceleration profiles in order to maximize the desired separation.
- the acceleration and/or deceleration phases of the spin are set to be slow in order to minimize vibrations that may occur during a quick acceleration and/or deceleration, in one aspect, the acceleration and/or deceleration phases of the spin are set to be fast in order to resolve a given class of lipoprotein; faster acceleration and/or deceleration settings may be used when the density/volume of one or more layers of the density gradient, particularly the bottom layer, is increased 1.25 g/ml or 1.0 ml, respectively.
- the acceleration and/or deceleration settings may range from 5 to 9 or 8 to 9 (with 9 being the slowest setting), In another aspect of this embodiment, the acceleration and/or deceleration settings may range from ⁇ to 5 or 2 to 4 (with 1 being the fastest setting.
- the foregoing settings are used when the sample has a triglyceride concentration of less than 150 mg/dL.
- the density gradient ultracentrifugation conditions are used to provide maximum resolution of LDL and IDL lipoproteins.
- the methods tor determining particle count employ obtaining a photometric measurement of a lipoprotein and determining a particle couni based on the photometric measurement.
- certain lipoprotein particle may provide a greater readout (or signal) when compared to another lipoprotein particle.
- the readout for equal numbers of lipoprotein particles may be greater for one lipoprotein particle than for another.
- IDL lipoprotein may be present in one or more fractions where LDL lipoprotein is present.
- IDL lipoprotein particle have several-fold greater light scattering properties than LDL lipoprotein particles.
- any IDL lipoprotein particles in a LDL fraction may lead to overestimation of the LDL particle number.
- Such mixing of IDL and LDL lipoprotein particles may occur when the I DL lipoprotein particle concentration in a sample is elevated.
- IDL lipoprotein particle concentrations are generally elevated when triglyceride concentrations are over 150 mg/dL, Therefore, alternate conditions for separation may be required when IDL particle concentrations are. elevated (such as, but not limited to, when triglyceride concentrations are over 150 mg/dL). in one embodiment, the following centrrfugations conditions are used when triglyceride concentrations are over 150 mg/dL.
- triglyceride concentration was less than 150 mg dL and greater than 150 mg/dL (see Fig. 7A- D).
- panels 7A and 7B represent the situation where triglyceride levels are less than 1 50 mg/dL (specifically 94 mg/dL) and panels 7C and 7D represent the situation where triglyceride levels are greater than 150 mg dL (specifically 437 mg dL).
- panels 7B and 7D represent the use of the centrifugation conditions referenced as Condition 1 above and panels 7A and 7C represent the use of the centrifugation conditions referenced as Condition 2 above (optimized for samples with triglyceride levels over 150 mg/dL).
- Examination of Fig. 7-A-D shows that the use of the centrifugation conditions referenced as Condition 2 above maintains the separation of lipoprotein particle fractions as compared to the use of Condition 3 above and provides accurate particle counts of the various lipoprotein classes (compare panels 7A and 7B).
- centrifugations conditions referenced as Condition 2 (7 A) above provided a LDL particle count of 1238 while the use of the centrifugations conditions referenced as Condition 1 (7B) above provided a LDL particle count of 1248. Furthermore, it is evident that the use of the centrifugation conditions referenced as Condition 2 above provides superior separation of the LDL and IDL lipoprotein particle fractions in the high triglyceride condition (compare panels 7C and 7D),
- the density gradient ultracentrifugation conditions are used to provide maximum resolution of HDL lipoproteins, In one embodiment, the following eentrif ligations conditions are used to provide maximal separation of HDL lipoproteins.
- FIGS. 8 A and 8B show the results of using the centrifugation conditions described as Condition 3.
- FIG. 8 A shows the concentration profile collected with a light scattering detector and
- FIG, 8B shows the corresponding deconvolved profile.
- the HDL peak is well resolved.
- the HDL peak is shifted to the right and an additional peak consisting of albumin and other proteins is resolved from the HDL peak.
- the Lp(a), LDL, IDL and VLDL peaks are ail compressed into a single peak to the far right of the profile.
- the density gradient ultracentrifugation conditions are used to provide maximum resolution of Lp(a) lipoproteins, In one embodiment, the following centrifugations conditions are used to provide maximal separation of Lp(a) lipoproteins.
- FIGS, 9A and 9B show the results of using the centrifugation conditions described as Condition 4.
- FIG, 9A shows the concentration profile collected with a light scattering detector and
- FIG. 9B shows the coiTesponding deconvoluted profile.
- the Lp(a) peak is well resolved.
- the Lp(a) peak is shifted to the left providing separation from other lipoprotein particles,
- An apparatus for quantifying lipoprotein particles in a plurality of serum lipid fractions.
- the apparatus generally functions by collecting lipoprotein fractions from a sample one traction at a time and transporting each fraction to a light scattering counter. The counter then measures the scattered light, which can be used to calculate the particle count for the fraction.
- a general embodiment of the apparatus comprises: a liquid conduit positioned to collect a sample from a sample vessel: and a light scattering counter positioned to receive the sample from the conduit.
- the sample is collected from the bottom of the sample vessel.
- the sample vessel may be any sample container known in the art.
- the sample vessel is a centrifuge tube.
- the use of a centrifuge tube has the advantage of using the same vessel for separation and for sampling.
- the centrifuge tube may have a bottom surface that is easily pierced by a sampler.
- a septum may be present on the bottom surface or the bottom surface may be a relatively thin structure.
- the liquid conduit may be any structure suitable for conveying the liquid in the sample to the light scattering counter. Examples of such structures include pipes, tubes, channels, hoses, or any other conduit suitable for carrying liquid as known in the art.
- the conduit is 8 mm (internal diameter) Teflon tubing.
- the liquid conduit will be positioned to collect the sample from the bottom of the vessel. This allows the collection of vertically stratified layers, as will occur when lipoprotein fractions are separated by density- gradient centrifugation.
- Some embodiments of the liquid conduit comprise a sampler connected to the conduit to facilitate collection of the sample.
- the liquid conduit is connected to a sampling needle.
- the sampling needle may be positioned to penetrate the sample vessel to as to allow the liquid from the sample vessel to flow through the needle into the conduit.
- the diameter of the tubing may be varied to obtain a suitable flow rate of sample; the length of the tubing and the relative elevation of the sample vessel and the counter will also affect the flow rate, as is understood by those skilled in the art. All of these factors may be varied as needed.
- the light scattering counter may be any suitable instrument, for example a laser light scattering counter. It may be configured to measure scattered light across any arc, as described above.
- the counter may comprise a flow cell, in which case the conduit may be connected to the flow cell so as to allow the liquid from the sample vessel to enter the flow cell wherein its light scattering properties will be measured.
- the apparatus may further comprise a pump configured to pump the sample through the conduit to the counter, Various types of pumps may be used.
- the pump is a piston pump, which allows good control over the flow rate of the liquid.
- the apparatus may comprise a sensor proximate to the conduit, wherein the sensor measures a fluid property within the conduit, and wherein said fluid property significantly differs in air and in liquid.
- the sensor is thus capable of distinguishing air from liquid in the conduit.
- Properties that can be used to distinguish air from liquid are well known in the art, and include thermal conductivity, electrical resistance, optical absorbance. and optical diffraction. Sensors capable of measuring these properties are well known in the art .
- the senor transmits a signal to indicate the presence of air in the conduit
- the sensor may send a signal to the pump to cease drawing iluid from the sample vessel when air is detected in the conduit
- the sensor is connected to transmit a signal to a valve positioned on the conduit. In such embodiments the sensor may send a signal to close the valve when air is detected in the conduit
- the apparatus may further comprise a data logger connected to the counter.
- the data logger may record the data either digitally or graphically (i.e., on a paper printout).
- the data may be further processed by a computing device, in some such embodiments the particle count for the lipoprotein fractions is computed by the computing device without direct human intervention. The resulting particle count may then be displayed or recorded.
- computer-readable media refers to a medium of storing information that is configured to be read by a machine. Such media include magnetic media, optical media, and paper media (punch cards, paper tape, etc.). Printed writing in a human language, if not intended or configured to be read by a machine, is not considered a computer-readable medium. In no case shall a human mind be construed as "computer-readable format.”
- the apparatus may also comprise a filter positioned on the conduit between the sample vessel and the counter.
- the filter functions to remove additional interfering particles.
- the pore size of the filter must be greater than the diameter of the lipoprotein to be counted, ideally the pore size of the filter will be only slightly greater than the diameter of the lipoprotein to be counted, although it is to be understood that most classes of lipoprotein show a range of sizes. Filters with 100 am pore size are quite suitable; they are readily available commercially and remove & ⁇ significant amount of interfering serum components without removing lipoproteins.
- Prefiltration may also be provided to remove larger particles to enhance the lifespan of a fine filter (such as the 100 nm fine filter described above); for example, a 2 ⁇ pore-size filter will effectively remove larger particles.
- the apparatus may comprise a reservoir of a cleaning fluid, such that the components of the apparatus may be flushed between samples
- the cleaning fluid may be as simple as saline solution, de-ionized water, saline made from filtered de- ionized water, or any of these with the addition of detergents and surfactants.
- a specific embodiment of the cleaning fluid is a 40% v/v solution of CleanzTM in water
- the reservoir may be connected to a cleaning conduit that joins the main conduit between the vaive and counter (downstream from the sensor and the sample vessel).
- the reservoir may be positioned above the components to be flushed to impart sufficient hydraulic head to cause the cleaning fluid to flow through the components under the force of gravity.
- a pump may be positioned to impart additional hydraulic head pressure to the cleaning fluid. While the vaive is open the fluid will flush the end of the conduit positioned to collect the sample, While the valve is closed the fluid will flow through the conduit to the counter,
- the apparatus may be in communication with a control unit.
- the control unit is in communication with the various components of the apparatus and may receive input from such components and/or control the operation of such components.
- the control unit may comprise the data logger, which as described above, receives the measurements of light scattering obtained from the light scattering counter.
- the control unit may contain executable programs to carry out functions associated with the methods described herein.
- the control unit may comprise an executable file used to deconvolute the data generated.
- the control unit may comprise an executable file that generates a particle number from the light scattering data measured.
- the executable file is or contains an algorithm described herein, in one embodiment, the control unit is a general purpose computer. The genera! purpose computer may be programmed to carry out the functions described.
- the apparatus comprises means for containing a liquid sample having vertically stratified fractions; means for conveying the lowest stratified fraction from the containing means; and means for counting particles configured to receive the lowest stratified traction from the containing means by way of the conveying means,
- the means for counter particles are means for measuring light scattering.
- the apparatus may comprise means for Hushing configured to flush the means for conveying and to flush the means for counting particles.
- the apparatus may also comprise means for sensing air within the conveying means.
- FIG. 10 an embodiment of the apparatus is presented comprising a sampling needle configured to puncture the bottom of a sample vessel; a tube having a first end and a second end, the first end connected to the sampling needle to receive a liquid sample from the needle; a light scattering counter connected to the second end of the tube and configured to measure light scattering in the sample when conveyed through the tube; an optical sensor positioned to measure the optical absorbance in the tube and capable of distinguishing air from liquid; a primary pump configured to pump the sample from the needle through the tube to the counter: a solenoid valve downstream of the sensor and connected to the sensor to receive an electrical signal causing the valve to close when air is detected by the sensor; and a flush reservoir connected to the tube.
- Measurements of lipoprotein particle count may be calibrated by comparing the results of other methods of counting or determining the concentration of lipoprotein particles to photometric data, Apo B is particularly useful in this regard for the atherogenic lipoproteins (Lp(a), LDL, IDL, or VLDL), as there is only one molecule of apoB present in a given particle of each atherogenic lipoprotein.
- Apo AI is particularly useful in this regard for the HDL, as there are only 2-5 molecules of Apo AI present in a given particle of HDL,; the exact number of Apo Al. molecules may be determined for each HDL particle, or an average number of Apo AI molecules per HDL particle may be used in the calculations described.
- a method for calibrating the measurement of a particle count of an lipoprotein comprising: (i) obtaining a photometric measurement of a lipoprotein from a calibration sample; (ii) measuring the molar concentration of specific marker, such as apoB for the atherogenic lipoproteins or Apo AI for HDL, in the lipoprotein fraction of the calibration sample; and (Hi) calculating a regression between the photometric measurement and the molar concentration of the marker,
- the atherogenic lipoprotein may be selected from the group consisting of: Lp(a), IDL, LDL, and YLDL
- the photometric measurement may be any disclosed above as suitable for determining the particle count of lipoproteins, including the measurement of light scattering.
- the regression may be an approximately linear regression, as would be expected between a measurement of light scattering and the particle count of a lipoprotein.
- the molar concentration of apoR, apoA! or other markers may be measured by various means known in the art, For example, commercially available immunoassays can be used to quickly and accurately measure the concentration of such markers in fractions containing lipoproteins from a sample. Such immunoassays may take any form in the art, including fluorescent, enzymatic and magnetic assays. One suitable assay is the Architect® system, available from Abbott Labs,
- the method may comprise obtaining a photometric measurement of the atherogenic lipoprotein from a second calibration sample; measuring the molar concentration of apoB in the second calibration sample; and calculating a regression based on the photometric measurement in the calibration sample, the molar concentration of apoB in the calibration sample, the photometric measurement in the second calibration sample, and the molar concentration of apoB in the second calibration sample. Additional measurements may be made as discussed above, as necessary to establish a sound regression.
- the present disclosure also provides for a method of determining the risk of atherogenic disease in a subject, the method comprising quantifying at least one serum lipoprotein in a sample from the subject according to the methods disclosed herein and comparing the results with known correlations between the at least one serum lipoprotein concentration and the risk of atherogenic disease.
- the method may further comprise obtaining a sample from the subject. Furthermore, the method may further comprise introducing the sample into an apparatus disclosed herein.
- the serum lipoprotein is LDL. In another embodiment, the serum lipoprotein is HDL. In still another embodiment, the serum lipoprotein is Lp(a). In still another embodiment, the serum lipoprotein is IDL. in still another embodiment, the serum lipoprotein is VLDL. In still another embodiment, the serum lipoprotein is LDL and HDL. in still another embodiment, the serum lipoprotein is LDL and IDL. In still another embodiment, the s&nim lipoprotein is LDL, IDL and VLDL. in still another embodiment, the serum lipoprotein is LDL, IDL VLDL, HDL, and Lp(a).
- a blood sample is collected from the subject.
- a sample is collected as is known in the art, such as in a serum separator tube (SST) or plain red top serum lube.
- Serum is separated according to standard procedure and filtered to remove any clots, fibrin and any large interfering particles.
- samples are subject to density gradient centrifugation to separate lipid components. Density gradients were prepared using either manual pipette and dispensing devices or an automated liquid handler (such as the Tecan GenesisTM). Multiple serum samples may be processed at one time, In one embodiment, a batch consisting of 16 serum samples is simultaneously prepared using an automated liquid handler. The following steps were used in the following examples:
- the apparatus is be an automated continuous flow through analysis system consisting of an automated specimen rack moving system, a tube piercing needle that can be automatically raised to pierce the tube, an end of sample drain detector, a sample valve that closes and opens automatically as programmed to facilitate the flow of sample from centrifuge tube, a piston pump to drain the sample from the centrifuge tube at a predetermined flow rate, a programmed pneumatic valve that allows the flow of baseline solution when sample is not flowing, a narrow bore (0.8 mm internal diameter) Teflon® tubing of a predetermined length (25 inches) that connects the pump to the muiti -angle laser light scattering flow through detector ( yatt Technology, Santa Barbara, CA) which outputs a light scattering signal proportional to the concentration of lipoprotein particles flowing through, an automated continuous flow through analysis system consisting of an automated specimen rack moving system, a tube piercing needle that can be automatically raised to pierce the tube, an end of sample drain detector, a sample valve that closes and opens automatically as programmed
- the sample is run at a flow rate of 3 mL per minute, using 25 inches of 0,8 mm TeflonTM tubing (resulting in a drain time of 1 minute 45 seconds).
- a laser impinges on the particles.
- the Wyatt instrument (DAWN HELEOS II) has 18 detectors (photodiodes) placed around the flow cell which collect signal from scattered light at their respective angles. The intensity of light is proportional to the type and number of lipoprotein particles flowing through. The signal is measured coming out of the detector placed at 90°.
- the method does not require any reagent, as it depends upon the physical phenomenon of light scattering. Such embodiments of the method simplify the instrumentation as well as reduce the cost of analysis. Analysis and Exemplary Results
- FIGS. 1 1-14 show the results of sample analysis using embodiments of the method and apparatus.
- FIG, 1 1 shows a normal lipid profile, showing three well- resolved peaks for the HDL, LDL, and VLDL fractions.
- FIG. 12 shows a high- LDL lipid profile, also showing three well-resolved peaks.
- FIG. 13 shows a high- Lp(a) lipid profile, in which the Lp(a) peak falls between the HDL peak and LDL peak; as can be seen the Lp(a) peak is quite visible.
- FIG, 14 shows a high-IDL, lipid profile, in which a pronounced IDL peak falls between the LDL peak and VLDL peak.
- the deconvolved profiles corresponding to FIGS, 1 1-14 are shown in Figures 15-18, respectively.
- the resulting deconvolved profiles have three major peaks for fractions of decreasing density going from left to right (as the time variable increases) corresponding to the HDL, LDL, and VLDL; and two minor peaks corresponding to Lp(a) and IDL as described above.
- Pool 1 had a triglyceride concentration of 70 mg/dL and an LDL. particle count of ⁇ 1G00 nraol/L
- Pool 2 had a triglyceride concentration of 70 mg/dL and an LDL particle count of > 1000 nmol/L
- Pool 3 had a triglyceride concentration of 21 8 mg dL and an LDL particle count of > 1900 nmol/L.
- Pool4 had a triglyceride concentration of 320 mg dL and an LDL particle count of >2100 nmol/L.
- IDL particle concentrations for pool 1 were 43 nmol/1, for pool 2 were 66 nmol/L, for pool 3 were 149 nmol/L and for pool 4 were 210 nmol/1.
- VLDL particle concentrations for pool 1 were 20 nmol/L, for pool 2 were 18 nmol/L, for pool 3 were 115 nmol/L and for pool 4 were 252 nmol/L.
- the results are expressed in coefficient of variation (%CV) within each day and between all days. The results for LDL, IDL and VLDL are shown below and show good reproducibility,
- the R 7 ' value for the plots were 0.996, 0.9890.998, 0.985 and 0.994, respectively for HDL, Lp(a), LDL, IDL and VLDL. This shows thai lipoprotein particle measurement is linear up to the tested ranges.
- the accuracy of the methods for determining lipoprotein particle concentration (number) was also evaluated. For LDL, two comparisons were made. First, comparison of average LDL particle concentration (number) was compared to serum apo B concentration. Second, comparison of average LDL particle concentration (number) was compared to LDL particle concentration (number) as measured by MR.
- each atherogenic lipid particle including LDL, contains one apo B molecule and therefore one can visualize direct comparison of LDL particle number to apo B concentration in an LDL fraction.
- a good correlation can be anticipated between LDL particle number and whole serum apo B, at least in normotriglyceriden ic subjects (triglyceride ⁇ 150 nig/dL), since >90% of apo B is known to be present in LDL particles. This correlation may be reduced as triglycerides concentration increases since each triglyceride-rich lipoprotein (IDL and VLDL) also contain one molecule of apo B.
- LDL particle number as determined by the meihods described herein was compared with serum apo B concentration in serum samples (SST) collected from 40 apparently healthy individuals (similar results were obtained when Condition i was used; data not shown).
- SST serum samples
- FIG. 24 shows a plot of the comparison of average LDL particle number obtained and apo B obtained from Abbott/ Architect C8000, The above results show a good correlation between LDL average particle number and serum apo B concentration.
- LDL particle count measured by the methods described herein does not include Lp(a) and IDL, which are generally considered components of LDL. it is not clear whether LDL particle numbers from NMR. method includes Lp(a) and or IDL, Thus, a high correlation and agreement between the two methods may not he expected. Moreover, the two methods are based on entirely two different principles.
- IDL and VLDL fractions comparison between the average lipoprotein particle counts was made using the concentration of cholesterol measure in the I DL and. VLDL fractions as determined by the YAP Assay (Atherotech. Inc., Birmingham, AL; methods described in US Patent Nos. 5,284,773 and 5,633,1 8, which, are hereby incorporated by reference for such teaching), IDL and VLDL particle number as determined by the methods described herein (using Condition 2 as the centrifugation condition) was compared with cholesterol content as determined by the VAP assay.
- HDL particle number as determined by the methods described herein (using Condition 3 as the centrifugation condition) was compared with serum apo AI concentration in serum samples (SST) collected from 88 individuals.
- the turbidimetry immunoassay by Abbott/Architect C8000 was used for serum apo AI measurement.
- FIG, 28 shows a plot of the comparison of average HDL particle number and apo AI obtained from Abbott/Architect C8000, The above results show a good correlation between HDL average particle number and serum apo ⁇ concentration. While the R value reported for HDL (0.63) was not as high as that reported for LDL, the lower correlation observed is likely a function of the heterogeneous nature of apo A distribution on HDL particles as compared to the homogenous distribution of apo B on LDL particles.
- Lp(a) particle number as determined by the methods described herein was compared with Lp(a) concentration in serum samples (SST) collected from. 78 individuals.
- the Lp(a) immunoassay by Randox Laboratories was used to measure Lp(a)
- FIG. 29 shows a plot of the comparison of average Lp(a) particle number as determined by the methods described herein and Lp(a) results obtained from the Randox immunoassay. The above results show a good correlation between Lp(a) average particle number and serum Lp(a) concentration.
- the decorrvolution algorithm used herein is based on plurality of basis of curves that can be manipulated to pro vide a best fit to any given lipoprotein profile. In one embodiment, there are multiply basis curves for a given lipoprotein class. In an alternate embodiment, there is a single curve for a given lipoprotein class. The number and location of the subcurves is based, in one embodiment, on empirical observation and testing with lipoprotein samples to determine a baseline for the analysis.
- 14 basis curves are used, in a particular embodiment, 14 basis curves are used, with 5 curves used for the HDL class, 1 curve for the Lp(a) class, 3 curves for the LDL class, 2 curves for the IDL class and 3 curves for the VLDL class.
- the fit is based on non-linear equations and involves one or more iterations to converge to a solution.
- the curves are based on a four parameter Weibull curve that has been used to describe particle size distribution,
- the Weibull equation is a well known equation commonly used in statistical and reliability calculations,
- the time scale of the profiles is normalized to a common scale, in one embodiment, the scale is arbitrarily set to G ⁇ 200.
- Each profile is segmented based on signals from the data set that uses the expected timing from separation procedure (such as uliracentrifugation) and morphological features found in the profile shapes,
- the Levenberg Marquadt is used to deconvolute the curves. This algorithm uses a search and step method to find a good fit for each curve. In one embodiment, all four parameters can be constrained to fit within a specified range, in particular, the range of motion along the X ⁇ Axis for each curve is constrained so thai the curves occupy a defined position based on the class of lipoprotein represented by the curve, In addition, the amplitude parameters are required to be positive.
Landscapes
- Health & Medical Sciences (AREA)
- Life Sciences & Earth Sciences (AREA)
- Chemical & Material Sciences (AREA)
- Engineering & Computer Science (AREA)
- Immunology (AREA)
- Physics & Mathematics (AREA)
- Pathology (AREA)
- General Physics & Mathematics (AREA)
- General Health & Medical Sciences (AREA)
- Biochemistry (AREA)
- Analytical Chemistry (AREA)
- Hematology (AREA)
- Biomedical Technology (AREA)
- Molecular Biology (AREA)
- Urology & Nephrology (AREA)
- Dispersion Chemistry (AREA)
- Food Science & Technology (AREA)
- Medicinal Chemistry (AREA)
- Biophysics (AREA)
- Microbiology (AREA)
- Cell Biology (AREA)
- Biotechnology (AREA)
- Endocrinology (AREA)
- Ecology (AREA)
- Investigating Or Analysing Biological Materials (AREA)
Abstract
Bien qu'une évaluation plus précise du risque de maladie cardiovasculaire chez une personne puisse être réalisée sur la base du nombre de particules lipoprotéiques par unité de volume dans le sang de cette personne, les méthodes actuelles sont toutes fondées sur la mesure de la masse de cholestérol lipoprotéique par unité de volume. La présente invention porte sur une numération rapide et précise des particules lipoprotéiques au moyen de la photométrie. L'invention concerne une méthode et un appareil permettant de mesurer le nombre de particules lipoprotéiques dans un échantillon au moyen de la photométrie.
Priority Applications (4)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
US14/408,527 US9702807B2 (en) | 2012-06-16 | 2013-06-17 | Measurement of serum lipoproteins |
US15/643,190 US10197492B2 (en) | 2012-06-16 | 2017-07-06 | Measurement of serum lipoproteins |
US16/256,017 US20190170632A1 (en) | 2012-06-16 | 2019-01-24 | Measurement of serum lipoproteins |
US16/577,923 US20200018686A1 (en) | 2012-06-16 | 2019-09-20 | Measurement of serum lipoproteins |
Applications Claiming Priority (6)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
US201261660710P | 2012-06-16 | 2012-06-16 | |
US61/660,710 | 2012-06-16 | ||
US13/842,577 US9239280B2 (en) | 2012-06-16 | 2013-03-15 | Measurement of serum lipoproteins |
US13/842,577 | 2013-03-15 | ||
US201361815503P | 2013-04-24 | 2013-04-24 | |
US61/815,503 | 2013-04-24 |
Related Parent Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
US13/842,577 Continuation-In-Part US9239280B2 (en) | 2012-06-16 | 2013-03-15 | Measurement of serum lipoproteins |
Related Child Applications (2)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
US14/408,527 A-371-Of-International US9702807B2 (en) | 2012-06-16 | 2013-06-17 | Measurement of serum lipoproteins |
US15/643,190 Continuation US10197492B2 (en) | 2012-06-16 | 2017-07-06 | Measurement of serum lipoproteins |
Publications (1)
Publication Number | Publication Date |
---|---|
WO2013188879A1 true WO2013188879A1 (fr) | 2013-12-19 |
Family
ID=66659041
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
PCT/US2013/046170 WO2013188879A1 (fr) | 2012-06-16 | 2013-06-17 | Mesure de lipoprotéines sériques |
Country Status (2)
Country | Link |
---|---|
US (4) | US9702807B2 (fr) |
WO (1) | WO2013188879A1 (fr) |
Cited By (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
WO2019110977A1 (fr) * | 2017-12-04 | 2019-06-13 | Oxford University Innovation Limited | Procédé de détermination de la concentration de lipoprotéines dans une solution à l'aide d'une diffusion de lumière |
CN112798481A (zh) * | 2020-10-27 | 2021-05-14 | 美康生物科技股份有限公司 | 一种用于检测脂蛋白颗粒浓度的试剂及其使用方法 |
Families Citing this family (3)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20150260631A1 (en) * | 2014-03-17 | 2015-09-17 | Health Diagnostic Laboratory, Inc. | System and method for assessing quanitites or sizes of lipoprotein particles from lipoprotein particle compositions |
EP3137891B1 (fr) * | 2014-04-28 | 2024-01-17 | DH Technologies Development Pte. Ltd. | Quantification de tracés multiples |
CN110108673A (zh) * | 2019-04-23 | 2019-08-09 | 江西维瑞生物科技有限公司 | 用于同时检测脂蛋白亚组分胆固醇和脂蛋白颗粒浓度的检测系统 |
Citations (6)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US5633168A (en) * | 1995-06-07 | 1997-05-27 | Glasscock; Larry M. | Controlled dispersion flow analysis system |
JP2002243745A (ja) * | 2001-02-15 | 2002-08-28 | Tosoh Corp | リポ蛋白質分析装置 |
JP3819895B2 (ja) * | 2003-10-29 | 2006-09-13 | 大塚電子株式会社 | 動脈硬化評価装置 |
US7521248B2 (en) * | 2007-04-20 | 2009-04-21 | Atherotech, Inc. | Apo B measurement system and method |
JP2010048703A (ja) * | 2008-08-22 | 2010-03-04 | Hokkaido Univ | 血清脂質の測定方法及び測定装置 |
US7856323B2 (en) * | 2006-08-11 | 2010-12-21 | Spectracell Laboratories, Inc. | Method for analyzing blood for lipoprotein components |
Family Cites Families (30)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US5128318A (en) * | 1987-05-20 | 1992-07-07 | The Rogosin Institute | Reconstituted HDL particles and uses thereof |
US4987085A (en) | 1987-06-22 | 1991-01-22 | Chemtrak Inc. | Blood filtering metering device |
US5187068A (en) * | 1989-06-09 | 1993-02-16 | Nicolae Luca | Method for determination of lipid moiety and apolipoprotein expressed epitope immunoreactivity on intact lipoprotein |
FR2684998B1 (fr) | 1991-12-11 | 1994-10-28 | Sebia Sa | Procede de separation de la lp(a) par electrophorese, gels pour la mise en óoeuvre de ce procede, et application a la determination in vitro du risque atherogene lie a la presence de la lp(a). |
US5460974A (en) | 1992-10-13 | 1995-10-24 | Miles Inc. | Method of assaying whole blood for HDL cholesterol |
US5766552A (en) | 1993-04-20 | 1998-06-16 | Actimed Laboratories, Inc. | Apparatus for red blood cell separation |
JP3356556B2 (ja) * | 1993-10-22 | 2002-12-16 | 第一化学薬品株式会社 | 変性リポプロテイン類の測定法 |
US5411053A (en) | 1994-07-01 | 1995-05-02 | Daniel A. Holt | Fluid pressure regulator |
US5589080A (en) | 1995-04-04 | 1996-12-31 | Cfr Corporation | Liquid recycling system with moving concentrated counterflow for filter clearance |
US5895869A (en) | 1995-11-17 | 1999-04-20 | Mwi, Inc. | Method and apparatus for analyzing particulate matter |
US5925229A (en) * | 1996-05-03 | 1999-07-20 | The Regents Of The University Of California | Low density lipoprotein fraction assay for cardiac disease risk |
US5872622A (en) | 1996-08-12 | 1999-02-16 | Met One, Inc. | Condensation nucleus counter having vapor stabilization and working fluid recovery |
CA2332699A1 (fr) * | 1998-07-07 | 2000-01-13 | Hisamitsu Pharmaceutical Co., Inc. | Oligonucleotides anti-sens ciblant l'il-15 |
US6267579B1 (en) * | 1998-12-23 | 2001-07-31 | Clinical Laboratory Development Group, Inc. | Apparatus for making a gradient gel |
US6212916B1 (en) | 1999-03-10 | 2001-04-10 | Sail Star Limited | Dry cleaning process and system using jet agitation |
WO2003025584A2 (fr) | 2001-02-05 | 2003-03-27 | The Board Of Regents For Oklahoma State University | Analyses directes de lipides seriques destinees a evaluer des etats pathologiques |
FI112825B (fi) | 2001-07-11 | 2004-01-15 | Antti Nissinen | Menetelmä alkoholinkulutuksen osoittamiseksi, menetelmässä käytettäviä välineitä sekä niiden valmistus |
EP1444526B1 (fr) | 2001-11-13 | 2011-09-21 | The Regents of The University of California | Analyse de mobilite ionique de particules biologiques |
US7416895B2 (en) * | 2002-06-21 | 2008-08-26 | Berkeley Heartlab, Inc. | Method for identifying at risk cardiovascular disease patients |
US7556034B2 (en) | 2003-04-03 | 2009-07-07 | Antonio Augusto De Miranda Grieco | Self-cleaning kitchen-range and assembly couplable to a surface |
US7700360B2 (en) | 2004-04-20 | 2010-04-20 | Kimberly-Clark Worldwide, Inc. | Optical method and system to determine distribution of lipid particles in a sample |
FR2869995B1 (fr) * | 2004-05-10 | 2006-09-22 | Sebia Sa | Procede ameliore de separation de proteines par electrophorese capillaire et compositions de tampon pour electrophorese capillaire |
WO2006057081A1 (fr) | 2004-11-24 | 2006-06-01 | Mitsuyo Okazaki | Methode d'analyse de lipoproteines |
EP2660482B1 (fr) | 2005-08-22 | 2019-08-07 | Life Technologies Corporation | Appareil, système et procédé utilisant des volumes discrets de fluides non miscibles |
US20080038762A1 (en) | 2006-08-11 | 2008-02-14 | Spectracell Laboratories, Inc. | Method for analyzing blood for lipoprotein components |
US8247235B2 (en) | 2007-06-08 | 2012-08-21 | Quest Diagnostics Investments Incorporated | Lipoprotein analysis by differential charged-particle mobility |
DK2939683T3 (en) | 2009-02-16 | 2017-03-13 | Cerenis Therapeutics Holding Sa | Apolipoprotein A-I mimetics |
AU2010250838B2 (en) * | 2009-05-20 | 2016-01-21 | Eth Zurich | Targeting microRNAs for metabolic disorders |
US9488666B2 (en) * | 2010-08-24 | 2016-11-08 | Helena Laboratories Corporation | Assay for determination of levels of lipoprotein particles in bodily fluids |
US20120244555A1 (en) * | 2011-03-24 | 2012-09-27 | University Of Rochester | Method of diagnosing mild traumatic brain injury |
-
2013
- 2013-06-17 WO PCT/US2013/046170 patent/WO2013188879A1/fr active Application Filing
- 2013-06-17 US US14/408,527 patent/US9702807B2/en not_active Expired - Fee Related
-
2017
- 2017-07-06 US US15/643,190 patent/US10197492B2/en active Active
-
2019
- 2019-01-24 US US16/256,017 patent/US20190170632A1/en not_active Abandoned
- 2019-09-20 US US16/577,923 patent/US20200018686A1/en not_active Abandoned
Patent Citations (6)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US5633168A (en) * | 1995-06-07 | 1997-05-27 | Glasscock; Larry M. | Controlled dispersion flow analysis system |
JP2002243745A (ja) * | 2001-02-15 | 2002-08-28 | Tosoh Corp | リポ蛋白質分析装置 |
JP3819895B2 (ja) * | 2003-10-29 | 2006-09-13 | 大塚電子株式会社 | 動脈硬化評価装置 |
US7856323B2 (en) * | 2006-08-11 | 2010-12-21 | Spectracell Laboratories, Inc. | Method for analyzing blood for lipoprotein components |
US7521248B2 (en) * | 2007-04-20 | 2009-04-21 | Atherotech, Inc. | Apo B measurement system and method |
JP2010048703A (ja) * | 2008-08-22 | 2010-03-04 | Hokkaido Univ | 血清脂質の測定方法及び測定装置 |
Non-Patent Citations (1)
Title |
---|
KULKARNI, K. R. ET AL.: "Quantification of cholesterol in all lipoprotein classes by the VAP-II method.", JOURNAL OF LIPID RESEARCH., vol. 35, no. L, 1994, pages 159 - 168 * |
Cited By (4)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
WO2019110977A1 (fr) * | 2017-12-04 | 2019-06-13 | Oxford University Innovation Limited | Procédé de détermination de la concentration de lipoprotéines dans une solution à l'aide d'une diffusion de lumière |
CN111684285A (zh) * | 2017-12-04 | 2020-09-18 | 牛津大学科技创新有限公司 | 利用光散射确定溶液中脂蛋白浓度的方法 |
CN112798481A (zh) * | 2020-10-27 | 2021-05-14 | 美康生物科技股份有限公司 | 一种用于检测脂蛋白颗粒浓度的试剂及其使用方法 |
WO2022088550A1 (fr) * | 2020-10-27 | 2022-05-05 | 美康生物科技股份有限公司 | Réactif de détection de la concentration de particules de lipoprotéine et procédé d'utilisation de réactif |
Also Published As
Publication number | Publication date |
---|---|
US20200018686A1 (en) | 2020-01-16 |
US9702807B2 (en) | 2017-07-11 |
US20170307504A1 (en) | 2017-10-26 |
US20190170632A1 (en) | 2019-06-06 |
US10197492B2 (en) | 2019-02-05 |
US20150146205A1 (en) | 2015-05-28 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
US20200018686A1 (en) | Measurement of serum lipoproteins | |
US20170322135A1 (en) | Measurement of serum lipoproteins | |
CA2808821C (fr) | Dosage destine a determiner les niveaux de particules de lipoproteines dans des liquides corporels | |
Jialal et al. | Comparison of an immunoprecipitation method for direct measurement of LDL-cholesterol with beta-quantification (ultracentrifugation) | |
US8247235B2 (en) | Lipoprotein analysis by differential charged-particle mobility | |
Biesalski et al. | Diagnosis of nutritional anemia—laboratory assessment of iron status | |
WO1994006021A1 (fr) | Determination de la concentration en lipoproteines dans le sang par analyse d'ecoulement a dispersion regulee | |
US7521248B2 (en) | Apo B measurement system and method | |
US11137410B2 (en) | Prognostic assays for maintenance hemodialysis patients | |
De Haene et al. | Comparison of triglyceride concentration with lipemic index in disorders of triglyceride and glycerol metabolism | |
Kocak et al. | Assessment of serum indices implementation on Roche Cobas 6000 Analyzer | |
US7856323B2 (en) | Method for analyzing blood for lipoprotein components | |
Sen et al. | A study on effect of lipemia on electrolyte measurement by direct ion selective electrode method | |
JP2023063389A (ja) | 原発性胆汁性胆管炎の検出を補助する方法 | |
Stephen et al. | Analytical comparison between microhematocrit and automated methods for packed cell volume (PCV) determination | |
EP2310848A2 (fr) | Caractérisation d' échantillons biologiques | |
JP2002090365A5 (ja) | 腎障害の検査方法 | |
Rajput et al. | Ultracentrifugation as a tool for removal of interference caused by lipemia in liver function test | |
US20110178718A1 (en) | Characterization of biological samples | |
Pannu et al. | Warfarin related nephropathy: a case report from a tertiary hospital of north India and review of literature | |
Al-Kufaishi et al. | Comparative Study of Electrolyte Levels in Hyperlipaemia Cases by Using Spectrophotometry and Ion Selective Electrode Techniques | |
Gebhardt et al. | A semi-automated and standardized method of determining the lamellar body content of amniotic fluid | |
RU2014615C1 (ru) | Способ диагностики дислипопротеидемии | |
Voutilainen et al. | Isolation And Determination of Lipoproteins | |
Henriquez | Fluorometric sedimentation equilibrium for lipoprotein sub-class analysis |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
121 | Ep: the epo has been informed by wipo that ep was designated in this application |
Ref document number: 13804737 Country of ref document: EP Kind code of ref document: A1 |
|
NENP | Non-entry into the national phase |
Ref country code: DE |
|
WWE | Wipo information: entry into national phase |
Ref document number: 14408527 Country of ref document: US |
|
122 | Ep: pct application non-entry in european phase |
Ref document number: 13804737 Country of ref document: EP Kind code of ref document: A1 |